Initial commit: SherpaOnnx2Pass 双通道 ASR 安卓工程(含说话人区分)

This commit is contained in:
liwenhao2 2026-09-10 14:47:15 +08:00
commit 80d3f59ecf
62 changed files with 4892 additions and 0 deletions

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*.iml
.gradle
/local.properties
/.idea/caches
/.idea/libraries
/.idea/modules.xml
/.idea/workspace.xml
/.idea/navEditor.xml
/.idea/assetWizardSettings.xml
.DS_Store
/build
/captures
.externalNativeBuild
.cxx
local.properties
# 模型文件体积大,不入库;运行时手动放入 app/src/main/assets/
*.onnx

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# Default ignored files
/shelf/
/workspace.xml

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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
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<option name="providerId" value="com.android.tools.idea.GradleProjectSystem" />
</component>
</project>

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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="deploymentTargetSelector">
<selectionStates>
<SelectionState runConfigName="app">
<option name="selectionMode" value="DROPDOWN" />
<DialogSelection />
</SelectionState>
</selectionStates>
</component>
</project>

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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="GradleMigrationSettings" migrationVersion="1" />
<component name="GradleSettings">
<option name="linkedExternalProjectsSettings">
<GradleProjectSettings>
<option name="testRunner" value="CHOOSE_PER_TEST" />
<option name="externalProjectPath" value="$PROJECT_DIR$" />
<option name="gradleJvm" value="#GRADLE_LOCAL_JAVA_HOME" />
<option name="modules">
<set>
<option value="$PROJECT_DIR$" />
<option value="$PROJECT_DIR$/app" />
</set>
</option>
</GradleProjectSettings>
</option>
</component>
</project>

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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="ProjectMigrations">
<option name="MigrateToGradleLocalJavaHome">
<set>
<option value="$PROJECT_DIR$" />
</set>
</option>
</component>
</project>

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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="ExternalStorageConfigurationManager" enabled="true" />
<component name="ProjectRootManager" version="2" languageLevel="JDK_17" default="true" project-jdk-name="ms-17" project-jdk-type="JavaSDK">
<output url="file://$PROJECT_DIR$/build/classes" />
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<component name="ProjectType">
<option name="id" value="Android" />
</component>
</project>

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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="RunConfigurationProducerService">
<option name="ignoredProducers">
<set>
<option value="com.intellij.execution.junit.AbstractAllInDirectoryConfigurationProducer" />
<option value="com.intellij.execution.junit.AllInPackageConfigurationProducer" />
<option value="com.intellij.execution.junit.PatternConfigurationProducer" />
<option value="com.intellij.execution.junit.TestInClassConfigurationProducer" />
<option value="com.intellij.execution.junit.UniqueIdConfigurationProducer" />
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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="VcsDirectoryMappings">
<mapping directory="$PROJECT_DIR$/../.." vcs="Git" />
<mapping directory="$PROJECT_DIR$" vcs="Git" />
</component>
</project>

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/build

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plugins {
id 'com.android.application'
id 'org.jetbrains.kotlin.android'
}
android {
namespace 'com.k2fsa.sherpa.onnx'
compileSdk 32
defaultConfig {
applicationId "com.k2fsa.sherpa.onnx"
minSdk 21
targetSdk 32
versionCode 20260901
versionName "1.13.7"
testInstrumentationRunner "androidx.test.runner.AndroidJUnitRunner"
// Only ship the ABIs actually needed: arm64 real devices + x86_64
// emulator. (Drop 'x86_64' too if you never use the emulator.)
ndk {
abiFilters 'arm64-v8a', 'x86_64'
}
}
// Store .onnx models uncompressed in the APK. Compressed assets must be
// inflated stream-by-stream at load time, which makes the 2+ GB model set
// dramatically slower to initialize (and can trip the 5s ANR timer).
androidResources {
noCompress 'onnx'
}
buildTypes {
release {
minifyEnabled false
proguardFiles getDefaultProguardFile('proguard-android-optimize.txt'), 'proguard-rules.pro'
}
}
compileOptions {
sourceCompatibility JavaVersion.VERSION_1_8
targetCompatibility JavaVersion.VERSION_1_8
}
kotlinOptions {
jvmTarget = '1.8'
}
}
dependencies {
implementation 'androidx.core:core-ktx:1.7.0'
implementation 'androidx.appcompat:appcompat:1.5.1'
implementation 'com.google.android.material:material:1.7.0'
implementation 'androidx.constraintlayout:constraintlayout:2.1.4'
testImplementation 'junit:junit:4.13.2'
androidTestImplementation 'androidx.test.ext:junit:1.1.4'
androidTestImplementation 'androidx.test.espresso:espresso-core:3.5.0'
}

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# Add project specific ProGuard rules here.
# You can control the set of applied configuration files using the
# proguardFiles setting in build.gradle.
#
# For more details, see
# http://developer.android.com/guide/developing/tools/proguard.html
# If your project uses WebView with JS, uncomment the following
# and specify the fully qualified class name to the JavaScript interface
# class:
#-keepclassmembers class fqcn.of.javascript.interface.for.webview {
# public *;
#}
# Uncomment this to preserve the line number information for
# debugging stack traces.
#-keepattributes SourceFile,LineNumberTable
# If you keep the line number information, uncomment this to
# hide the original source file name.
#-renamesourcefileattribute SourceFile

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package com.k2fsa.sherpa.onnx
import androidx.test.platform.app.InstrumentationRegistry
import androidx.test.ext.junit.runners.AndroidJUnit4
import org.junit.Test
import org.junit.runner.RunWith
import org.junit.Assert.*
/**
* Instrumented test, which will execute on an Android device.
*
* See [testing documentation](http://d.android.com/tools/testing).
*/
@RunWith(AndroidJUnit4::class)
class ExampleInstrumentedTest {
@Test
fun useAppContext() {
// Context of the app under test.
val appContext = InstrumentationRegistry.getInstrumentation().targetContext
assertEquals("com.k2fsa.sherpa.onnx", appContext.packageName)
}
}

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*.so

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<?xml version="1.0" encoding="utf-8"?>
<manifest xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:tools="http://schemas.android.com/tools">
<uses-permission android:name="android.permission.RECORD_AUDIO" />
<application
android:allowBackup="true"
android:dataExtractionRules="@xml/data_extraction_rules"
android:fullBackupContent="@xml/backup_rules"
android:icon="@mipmap/ic_launcher"
android:label="@string/app_name"
android:roundIcon="@mipmap/ic_launcher_round"
android:supportsRtl="true"
android:theme="@style/Theme.SherpaOnnx2Pass"
tools:targetApi="31">
<activity
android:name=".MainActivity"
android:label="2pass ASR: Next-gen Kaldi"
android:exported="true">
<intent-filter>
<action android:name="android.intent.action.MAIN" />
<category android:name="android.intent.category.LAUNCHER" />
</intent-filter>
<meta-data
android:name="android.app.lib_name"
android:value="" />
</activity>
</application>
</manifest>

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package com.k2fsa.sherpa.onnx
data class FeatureConfig(
var sampleRate: Int = 16000,
var featureDim: Int = 80,
var dither: Float = 0.0f
)
fun getFeatureConfig(sampleRate: Int, featureDim: Int): FeatureConfig {
return FeatureConfig(sampleRate = sampleRate, featureDim = featureDim)
}

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package com.k2fsa.sherpa.onnx
data class HomophoneReplacerConfig(
var dictDir: String = "", // unused
var lexicon: String = "",
var ruleFsts: String = "",
)

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package com.k2fsa.sherpa.onnx
class OfflineStream(var ptr: Long) {
init {
require(ptr != 0L) { "Failed to create native OfflineStream" }
}
fun acceptWaveform(samples: FloatArray, sampleRate: Int) =
acceptWaveform(ptr, samples, sampleRate)
fun setOption(key: String, value: String) = setOption(ptr, key, value)
fun getOption(key: String): String = getOption(ptr, key)
protected fun finalize() {
if (ptr != 0L) {
delete(ptr)
ptr = 0
}
}
fun release() = finalize()
fun use(block: (OfflineStream) -> Unit) {
try {
block(this)
} finally {
release()
}
}
private external fun acceptWaveform(ptr: Long, samples: FloatArray, sampleRate: Int)
private external fun setOption(ptr: Long, key: String, value: String)
private external fun getOption(ptr: Long, key: String): String
private external fun delete(ptr: Long)
companion object {
init {
System.loadLibrary("sherpa-onnx-jni")
}
}
}

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package com.k2fsa.sherpa.onnx
import android.content.res.AssetManager
data class EndpointRule(
var mustContainNonSilence: Boolean,
var minTrailingSilence: Float,
var minUtteranceLength: Float,
)
data class EndpointConfig(
var rule1: EndpointRule = EndpointRule(false, 2.4f, 0.0f),
var rule2: EndpointRule = EndpointRule(true, 1.4f, 0.0f),
var rule3: EndpointRule = EndpointRule(false, 0.0f, 20.0f)
)
data class OnlineTransducerModelConfig(
var encoder: String = "",
var decoder: String = "",
var joiner: String = "",
var qnnConfig: QnnConfig = QnnConfig(),
)
data class OnlineParaformerModelConfig(
var encoder: String = "",
var decoder: String = "",
)
data class OnlineZipformer2CtcModelConfig(
var model: String = "",
)
data class OnlineNeMoCtcModelConfig(
var model: String = "",
)
data class OnlineToneCtcModelConfig(
var model: String = "",
)
data class OnlineModelConfig(
var transducer: OnlineTransducerModelConfig = OnlineTransducerModelConfig(),
var paraformer: OnlineParaformerModelConfig = OnlineParaformerModelConfig(),
var zipformer2Ctc: OnlineZipformer2CtcModelConfig = OnlineZipformer2CtcModelConfig(),
var neMoCtc: OnlineNeMoCtcModelConfig = OnlineNeMoCtcModelConfig(),
var toneCtc: OnlineToneCtcModelConfig = OnlineToneCtcModelConfig(),
var tokens: String = "",
var numThreads: Int = 1,
var debug: Boolean = false,
var provider: String = "cpu",
var modelType: String = "",
var modelingUnit: String = "",
var bpeVocab: String = "",
)
data class OnlineLMConfig(
var model: String = "",
var scale: Float = 0.5f,
)
data class OnlineCtcFstDecoderConfig(
var graph: String = "",
var maxActive: Int = 3000,
)
data class OnlineRecognizerConfig(
var featConfig: FeatureConfig = FeatureConfig(),
var modelConfig: OnlineModelConfig = OnlineModelConfig(),
var lmConfig: OnlineLMConfig = OnlineLMConfig(),
var ctcFstDecoderConfig: OnlineCtcFstDecoderConfig = OnlineCtcFstDecoderConfig(),
var hr: HomophoneReplacerConfig = HomophoneReplacerConfig(),
var endpointConfig: EndpointConfig = EndpointConfig(),
var enableEndpoint: Boolean = true,
var decodingMethod: String = "greedy_search",
var maxActivePaths: Int = 4,
var hotwordsFile: String = "",
var hotwordsScore: Float = 1.5f,
var ruleFsts: String = "",
var ruleFars: String = "",
var blankPenalty: Float = 0.0f,
)
data class OnlineRecognizerResult(
val text: String,
val tokens: Array<String>,
val timestamps: FloatArray,
val ysProbs: FloatArray,
// TODO(fangjun): Add more fields
)
class OnlineRecognizer(
assetManager: AssetManager? = null,
val config: OnlineRecognizerConfig,
) {
private var ptr: Long
init {
ptr = if (assetManager != null) {
newFromAsset(assetManager, config)
} else {
newFromFile(config)
}
require(ptr != 0L) {
"Invalid OnlineRecognizerConfig: failed to create native OnlineRecognizer"
}
}
protected fun finalize() {
if (ptr != 0L) {
delete(ptr)
ptr = 0
}
}
fun release() = finalize()
fun createStream(hotwords: String = ""): OnlineStream {
val p = createStream(ptr, hotwords)
return OnlineStream(p)
}
fun reset(stream: OnlineStream) = reset(ptr, stream.ptr)
fun decode(stream: OnlineStream) = decode(ptr, stream.ptr)
fun isEndpoint(stream: OnlineStream) = isEndpoint(ptr, stream.ptr)
fun isReady(stream: OnlineStream) = isReady(ptr, stream.ptr)
fun getResult(stream: OnlineStream): OnlineRecognizerResult {
return getResult(ptr, stream.ptr)
}
private external fun delete(ptr: Long)
private external fun newFromAsset(
assetManager: AssetManager,
config: OnlineRecognizerConfig,
): Long
private external fun newFromFile(
config: OnlineRecognizerConfig,
): Long
private external fun createStream(ptr: Long, hotwords: String): Long
private external fun reset(ptr: Long, streamPtr: Long)
private external fun decode(ptr: Long, streamPtr: Long)
private external fun isEndpoint(ptr: Long, streamPtr: Long): Boolean
private external fun isReady(ptr: Long, streamPtr: Long): Boolean
private external fun getResult(ptr: Long, streamPtr: Long): OnlineRecognizerResult
companion object {
init {
System.loadLibrary("sherpa-onnx-jni")
}
@JvmStatic
external fun prependAdspLibraryPath(newPath: String) // for qnn
}
}
/*
Please see
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html
for a list of pre-trained models.
We only add a few here. Please change the following code
to add your own. (It should be straightforward to add a new model
by following the code)
@param type
0 - sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20 (Bilingual, Chinese + English)
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/zipformer-transducer-models.html#sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20-bilingual-chinese-english
1 - csukuangfj/sherpa-onnx-lstm-zh-2023-02-20 (Chinese)
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/lstm-transducer-models.html#csukuangfj-sherpa-onnx-lstm-zh-2023-02-20-chinese
2 - csukuangfj/sherpa-onnx-lstm-en-2023-02-17 (English)
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/lstm-transducer-models.html#csukuangfj-sherpa-onnx-lstm-en-2023-02-17-english
3,4 - pkufool/icefall-asr-zipformer-streaming-wenetspeech-20230615
https://huggingface.co/pkufool/icefall-asr-zipformer-streaming-wenetspeech-20230615
3 - int8 encoder
4 - float32 encoder
5 - csukuangfj/sherpa-onnx-streaming-paraformer-bilingual-zh-en
https://huggingface.co/csukuangfj/sherpa-onnx-streaming-paraformer-bilingual-zh-en
6 - sherpa-onnx-streaming-zipformer-en-2023-06-26
https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-en-2023-06-26
7 - shaojieli/sherpa-onnx-streaming-zipformer-fr-2023-04-14 (French)
https://huggingface.co/shaojieli/sherpa-onnx-streaming-zipformer-fr-2023-04-14
8 - csukuangfj/sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20 (Bilingual, Chinese + English)
https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20
encoder int8, decoder/joiner float32
9025 - sherpa-onnx-qnn-streaming-zipformer-transducer-zh-en-2023-03-20-chunk-size-32-android-aarch64
QNN model libs with writable binary context files
libencoder.so, libdecoder.so, libjoiner.so
9026 - sherpa-onnx-qnn-SM8850-binary-streaming-zipformer-transducer-zh-en-2023-03-20-chunk-size-32
QNN binary context files only
encoder.bin, decoder.bin, joiner.bin
*/
fun getModelConfig(type: Int, modelPrefix: String = ""): OnlineModelConfig? {
when (type) {
0 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder-epoch-99-avg-1.onnx",
decoder = "$modelDir/decoder-epoch-99-avg-1.onnx",
joiner = "$modelDir/joiner-epoch-99-avg-1.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer",
)
}
1 -> {
val modelDir = "sherpa-onnx-lstm-zh-2023-02-20"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder-epoch-11-avg-1.onnx",
decoder = "$modelDir/decoder-epoch-11-avg-1.onnx",
joiner = "$modelDir/joiner-epoch-11-avg-1.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "lstm",
)
}
2 -> {
val modelDir = "sherpa-onnx-lstm-en-2023-02-17"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder-epoch-99-avg-1.onnx",
decoder = "$modelDir/decoder-epoch-99-avg-1.onnx",
joiner = "$modelDir/joiner-epoch-99-avg-1.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "lstm",
)
}
3 -> {
val modelDir = "icefall-asr-zipformer-streaming-wenetspeech-20230615"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/exp/encoder-epoch-12-avg-4-chunk-16-left-128.int8.onnx",
decoder = "$modelDir/exp/decoder-epoch-12-avg-4-chunk-16-left-128.onnx",
joiner = "$modelDir/exp/joiner-epoch-12-avg-4-chunk-16-left-128.onnx",
),
tokens = "$modelDir/data/lang_char/tokens.txt",
modelType = "zipformer2",
)
}
4 -> {
val modelDir = "icefall-asr-zipformer-streaming-wenetspeech-20230615"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/exp/encoder-epoch-12-avg-4-chunk-16-left-128.onnx",
decoder = "$modelDir/exp/decoder-epoch-12-avg-4-chunk-16-left-128.onnx",
joiner = "$modelDir/exp/joiner-epoch-12-avg-4-chunk-16-left-128.onnx",
),
tokens = "$modelDir/data/lang_char/tokens.txt",
modelType = "zipformer2",
)
}
5 -> {
val modelDir = "sherpa-onnx-streaming-paraformer-bilingual-zh-en"
return OnlineModelConfig(
paraformer = OnlineParaformerModelConfig(
encoder = "$modelDir/encoder.int8.onnx",
decoder = "$modelDir/decoder.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "paraformer",
)
}
6 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-en-2023-06-26"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder-epoch-99-avg-1-chunk-16-left-128.int8.onnx",
decoder = "$modelDir/decoder-epoch-99-avg-1-chunk-16-left-128.onnx",
joiner = "$modelDir/joiner-epoch-99-avg-1-chunk-16-left-128.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer2",
)
}
7 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-fr-2023-04-14"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder-epoch-29-avg-9-with-averaged-model.int8.onnx",
decoder = "$modelDir/decoder-epoch-29-avg-9-with-averaged-model.onnx",
joiner = "$modelDir/joiner-epoch-29-avg-9-with-averaged-model.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer",
)
}
8 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder-epoch-99-avg-1.int8.onnx",
decoder = "$modelDir/decoder-epoch-99-avg-1.onnx",
joiner = "$modelDir/joiner-epoch-99-avg-1.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer",
)
}
9 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-zh-14M-2023-02-23"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder-epoch-99-avg-1.int8.onnx",
decoder = "$modelDir/decoder-epoch-99-avg-1.onnx",
joiner = "$modelDir/joiner-epoch-99-avg-1.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer",
)
}
10 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-en-20M-2023-02-17"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder-epoch-99-avg-1.int8.onnx",
decoder = "$modelDir/decoder-epoch-99-avg-1.onnx",
joiner = "$modelDir/joiner-epoch-99-avg-1.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer",
)
}
11 -> {
val modelDir = "sherpa-onnx-nemo-streaming-fast-conformer-ctc-en-80ms"
return OnlineModelConfig(
neMoCtc = OnlineNeMoCtcModelConfig(
model = "$modelDir/model.onnx",
),
tokens = "$modelDir/tokens.txt",
)
}
12 -> {
val modelDir = "sherpa-onnx-nemo-streaming-fast-conformer-ctc-en-480ms"
return OnlineModelConfig(
neMoCtc = OnlineNeMoCtcModelConfig(
model = "$modelDir/model.onnx",
),
tokens = "$modelDir/tokens.txt",
)
}
13 -> {
val modelDir = "sherpa-onnx-nemo-streaming-fast-conformer-ctc-en-1040ms"
return OnlineModelConfig(
neMoCtc = OnlineNeMoCtcModelConfig(
model = "$modelDir/model.onnx",
),
tokens = "$modelDir/tokens.txt",
)
}
14 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-korean-2024-06-16"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder-epoch-99-avg-1.int8.onnx",
decoder = "$modelDir/decoder-epoch-99-avg-1.onnx",
joiner = "$modelDir/joiner-epoch-99-avg-1.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer",
)
}
15 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-small-ctc-zh-int8-2025-04-01"
return OnlineModelConfig(
zipformer2Ctc = OnlineZipformer2CtcModelConfig(
model = "$modelDir/model.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
)
}
16 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-small-ctc-zh-2025-04-01"
return OnlineModelConfig(
zipformer2Ctc = OnlineZipformer2CtcModelConfig(
model = "$modelDir/model.onnx",
),
tokens = "$modelDir/tokens.txt",
)
}
17 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-ctc-zh-int8-2025-06-30"
return OnlineModelConfig(
zipformer2Ctc = OnlineZipformer2CtcModelConfig(
model = "$modelDir/model.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
)
}
18 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-ctc-zh-2025-06-30"
return OnlineModelConfig(
zipformer2Ctc = OnlineZipformer2CtcModelConfig(
model = "$modelDir/model.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer2",
)
}
19 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-ctc-zh-fp16-2025-06-30"
return OnlineModelConfig(
zipformer2Ctc = OnlineZipformer2CtcModelConfig(
model = "$modelDir/model.fp16.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer2",
)
}
20 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-zh-int8-2025-06-30"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder.int8.onnx",
decoder = "$modelDir/decoder.onnx",
joiner = "$modelDir/joiner.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer2",
)
}
21 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-en-kroko-2025-08-06"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder.onnx",
decoder = "$modelDir/decoder.onnx",
joiner = "$modelDir/joiner.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer2",
)
}
22 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-es-kroko-2025-08-06"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder.onnx",
decoder = "$modelDir/decoder.onnx",
joiner = "$modelDir/joiner.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer2",
)
}
23 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-fr-kroko-2025-08-06"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder.onnx",
decoder = "$modelDir/decoder.onnx",
joiner = "$modelDir/joiner.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer2",
)
}
24 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-de-kroko-2025-08-06"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder.onnx",
decoder = "$modelDir/decoder.onnx",
joiner = "$modelDir/joiner.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer2",
)
}
25 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-small-ru-vosk-int8-2025-08-16"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder.int8.onnx",
decoder = "$modelDir/decoder.onnx",
joiner = "$modelDir/joiner.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer2",
)
}
26 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-small-ru-vosk-2025-08-16"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder.onnx",
decoder = "$modelDir/decoder.onnx",
joiner = "$modelDir/joiner.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer2",
)
}
27 -> {
val modelDir = "sherpa-onnx-streaming-t-one-russian-2025-09-08"
return OnlineModelConfig(
toneCtc = OnlineToneCtcModelConfig(
model = "$modelDir/model.onnx",
),
tokens = "$modelDir/tokens.txt",
)
}
28 -> {
val modelDir = "sherpa-onnx-nemotron-speech-streaming-en-0.6b-int8-2026-01-14"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder.int8.onnx",
decoder = "$modelDir/decoder.int8.onnx",
joiner = "$modelDir/joiner.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
)
}
29 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-bn-vosk-2026-02-09"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder.onnx",
decoder = "$modelDir/decoder.onnx",
joiner = "$modelDir/joiner.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer2",
)
}
30 -> {
val modelDir = "sherpa-onnx-nemotron-speech-streaming-en-0.6b-80ms-int8-2026-04-25"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder.int8.onnx",
decoder = "$modelDir/decoder.int8.onnx",
joiner = "$modelDir/joiner.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
)
}
31 -> {
val modelDir = "sherpa-onnx-nemotron-speech-streaming-en-0.6b-160ms-int8-2026-04-25"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder.int8.onnx",
decoder = "$modelDir/decoder.int8.onnx",
joiner = "$modelDir/joiner.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
)
}
32 -> {
val modelDir = "sherpa-onnx-nemotron-speech-streaming-en-0.6b-560ms-int8-2026-04-25"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder.int8.onnx",
decoder = "$modelDir/decoder.int8.onnx",
joiner = "$modelDir/joiner.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
)
}
34 -> {
val modelDir = modelPrefix +
"sherpa-onnx-nemotron-3.5-asr-streaming-0.6b-560ms-int8-2026-06-11"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder.int8.onnx",
decoder = "$modelDir/decoder.int8.onnx",
joiner = "$modelDir/joiner.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
)
}
33 -> {
val modelDir = "sherpa-onnx-nemotron-speech-streaming-en-0.6b-1120ms-int8-2026-04-25"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder.int8.onnx",
decoder = "$modelDir/decoder.int8.onnx",
joiner = "$modelDir/joiner.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
)
}
9025 -> {
val modelDir =
"sherpa-onnx-qnn-streaming-zipformer-transducer-zh-en-2023-03-20-chunk-size-32-android-aarch64"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/libencoder.so",
decoder = "$modelDir/libdecoder.so",
joiner = "$modelDir/libjoiner.so",
qnnConfig = QnnConfig(
backendLib = "libQnnHtp.so",
systemLib = "libQnnSystem.so",
// The following three *.bin files are generated during the first run
// and are used to replace the corresponding *.so files in later runs
contextBinary = "$modelDir/encoder.bin,$modelDir/decoder.bin,$modelDir/joiner.bin",
),
),
tokens = "$modelDir/tokens.txt",
provider = "qnn",
modelType = "zipformer",
)
}
9026 -> {
// for Xiaomi 17 Pro
val modelDir =
"sherpa-onnx-qnn-SM8850-binary-streaming-zipformer-transducer-zh-en-2023-03-20-chunk-size-32"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
qnnConfig = QnnConfig(
backendLib = "libQnnHtp.so",
systemLib = "libQnnSystem.so",
contextBinary = "$modelDir/encoder.bin,$modelDir/decoder.bin,$modelDir/joiner.bin",
),
),
tokens = "$modelDir/tokens.txt",
provider = "qnn",
modelType = "zipformer",
)
}
9027 -> {
val modelDir =
"sherpa-onnx-qnn-x-asr-streaming-zipformer-transducer-zh-en-2026-06-05-chunk-size-480ms-android-aarch64"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/libencoder.so",
decoder = "$modelDir/libdecoder.so",
joiner = "$modelDir/libjoiner.so",
qnnConfig = QnnConfig(
backendLib = "libQnnHtp.so",
systemLib = "libQnnSystem.so",
contextBinary = "$modelDir/encoder.bin,$modelDir/decoder.bin,$modelDir/joiner.bin",
),
),
tokens = "$modelDir/tokens.txt",
provider = "qnn",
modelType = "zipformer",
)
}
9028 -> {
val modelDir =
"sherpa-onnx-qnn-x-asr-streaming-zipformer-transducer-zh-en-punct-2026-06-05-chunk-size-480ms-android-aarch64"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/libencoder.so",
decoder = "$modelDir/libdecoder.so",
joiner = "$modelDir/libjoiner.so",
qnnConfig = QnnConfig(
backendLib = "libQnnHtp.so",
systemLib = "libQnnSystem.so",
contextBinary = "$modelDir/encoder.bin,$modelDir/decoder.bin,$modelDir/joiner.bin",
),
),
tokens = "$modelDir/tokens.txt",
provider = "qnn",
modelType = "zipformer",
)
}
9029 -> {
// for Xiaomi 17 Pro
val modelDir =
"sherpa-onnx-qnn-SM8850-binary-x-asr-streaming-zipformer-transducer-zh-en-2026-06-05-chunk-size-480ms"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
qnnConfig = QnnConfig(
backendLib = "libQnnHtp.so",
systemLib = "libQnnSystem.so",
contextBinary = "$modelDir/encoder.bin,$modelDir/decoder.bin,$modelDir/joiner.bin",
),
),
tokens = "$modelDir/tokens.txt",
provider = "qnn",
modelType = "zipformer",
)
}
9030 -> {
// for Xiaomi 17 Pro
val modelDir =
"sherpa-onnx-qnn-SM8850-binary-x-asr-streaming-zipformer-transducer-zh-en-punct-2026-06-05-chunk-size-480ms"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
qnnConfig = QnnConfig(
backendLib = "libQnnHtp.so",
systemLib = "libQnnSystem.so",
contextBinary = "$modelDir/encoder.bin,$modelDir/decoder.bin,$modelDir/joiner.bin",
),
),
tokens = "$modelDir/tokens.txt",
provider = "qnn",
modelType = "zipformer",
)
}
1000 -> {
val modelDir = "sherpa-onnx-rk3588-streaming-zipformer-bilingual-zh-en-2023-02-20"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder.rknn",
decoder = "$modelDir/decoder.rknn",
joiner = "$modelDir/joiner.rknn",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer",
provider = "rknn",
)
}
1001 -> {
val modelDir = "sherpa-onnx-rk3588-streaming-zipformer-small-bilingual-zh-en-2023-02-16"
return OnlineModelConfig(
transducer = OnlineTransducerModelConfig(
encoder = "$modelDir/encoder.rknn",
decoder = "$modelDir/decoder.rknn",
joiner = "$modelDir/joiner.rknn",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer",
provider = "rknn",
)
}
}
return null
}
/*
Please see
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html
for a list of pre-trained models.
We only add a few here. Please change the following code
to add your own LM model. (It should be straightforward to train a new NN LM model
by following the code, https://github.com/k2-fsa/icefall/blob/master/icefall/rnn_lm/train.py)
@param type
0 - sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20 (Bilingual, Chinese + English)
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/zipformer-transducer-models.html#sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20-bilingual-chinese-english
*/
fun getOnlineLMConfig(type: Int): OnlineLMConfig {
when (type) {
0 -> {
val modelDir = "sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20"
return OnlineLMConfig(
model = "$modelDir/with-state-epoch-99-avg-1.int8.onnx",
scale = 0.5f,
)
}
}
return OnlineLMConfig()
}
fun getEndpointConfig(): EndpointConfig {
return EndpointConfig(
rule1 = EndpointRule(false, 2.4f, 0.0f),
rule2 = EndpointRule(true, 1.4f, 0.0f),
rule3 = EndpointRule(false, 0.0f, 20.0f)
)
}

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@ -0,0 +1,46 @@
package com.k2fsa.sherpa.onnx
class OnlineStream(var ptr: Long = 0) {
init {
require(ptr != 0L) { "Failed to create native OnlineStream" }
}
fun acceptWaveform(samples: FloatArray, sampleRate: Int) =
acceptWaveform(ptr, samples, sampleRate)
fun inputFinished() = inputFinished(ptr)
fun setOption(key: String, value: String) = setOption(ptr, key, value)
fun getOption(key: String): String = getOption(ptr, key)
protected fun finalize() {
if (ptr != 0L) {
delete(ptr)
ptr = 0
}
}
fun release() = finalize()
fun use(block: (OnlineStream) -> Unit) {
try {
block(this)
} finally {
release()
}
}
private external fun acceptWaveform(ptr: Long, samples: FloatArray, sampleRate: Int)
private external fun inputFinished(ptr: Long)
private external fun setOption(ptr: Long, key: String, value: String)
private external fun getOption(ptr: Long, key: String): String
private external fun delete(ptr: Long)
companion object {
init {
System.loadLibrary("sherpa-onnx-jni")
}
}
}

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@ -0,0 +1,7 @@
package com.k2fsa.sherpa.onnx
data class QnnConfig(
var backendLib: String = "",
var contextBinary: String = "",
var systemLib: String = "",
)

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@ -0,0 +1,235 @@
package com.k2fsa.sherpa.onnx
import android.content.res.AssetManager
import android.util.Log
import kotlin.math.sqrt
// ---------------------------------------------------------------------------
// Native speaker-embedding extractor (wraps libsherpa-onnx-jni).
// Ported from android/SherpaOnnxSpeakerIdentification so both apps stay
// compatible with the same JNI symbols.
// ---------------------------------------------------------------------------
class SpeakerEmbeddingExtractor(
assetManager: AssetManager? = null,
config: SpeakerEmbeddingExtractorConfig,
) {
private var ptr: Long
init {
ptr = if (assetManager != null) {
newFromAsset(assetManager, config)
} else {
newFromFile(config)
}
require(ptr != 0L) {
"Invalid SpeakerEmbeddingExtractorConfig: failed to create native SpeakerEmbeddingExtractor"
}
}
protected fun finalize() {
if (ptr != 0L) {
delete(ptr)
ptr = 0
}
}
fun release() = finalize()
fun createStream(): OnlineStream {
val p = createStream(ptr)
return OnlineStream(p)
}
fun isReady(stream: OnlineStream) = isReady(ptr, stream.ptr)
fun compute(stream: OnlineStream) = compute(ptr, stream.ptr)
fun dim() = dim(ptr)
private external fun newFromAsset(
assetManager: AssetManager,
config: SpeakerEmbeddingExtractorConfig,
): Long
private external fun newFromFile(config: SpeakerEmbeddingExtractorConfig): Long
private external fun delete(ptr: Long)
private external fun createStream(ptr: Long): Long
private external fun isReady(ptr: Long, streamPtr: Long): Boolean
private external fun compute(ptr: Long, streamPtr: Long): FloatArray
private external fun dim(ptr: Long): Int
companion object {
init {
System.loadLibrary("sherpa-onnx-jni")
}
}
}
// ---------------------------------------------------------------------------
// SpeakerRegistry: lightweight in-Kotlin speaker store + cosine matching.
//
// We avoid the native SpeakerEmbeddingManager on purpose: it cannot rename a
// speaker once enrolled, which we need for the "auto-label then assign a real
// name" flow. Matching here prefers named entries over auto (S0/S1/...) ones.
// ---------------------------------------------------------------------------
class SpeakerRegistry {
private val named = ArrayList<Pair<String, FloatArray>>()
private val auto = ArrayList<Pair<String, FloatArray>>()
val namedNames: List<String>
get() = named.map { it.first }
// The rolling window checker runs on its own thread while the endpoint
// identification runs on the recording thread: serialize everything.
@Synchronized
fun clear() {
named.clear()
auto.clear()
}
// Returns the best label for embedding `e`, or null if no speaker is close
// enough (below threshold). Registered names win ties against auto labels.
@Synchronized
fun search(e: FloatArray, threshold: Float): String? {
match(named, e, threshold)?.let { return it }
match(auto, e, threshold)?.let { return it }
return null
}
@Synchronized
fun addAuto(name: String, e: FloatArray) {
auto.add(Pair(name, l2normalize(e)))
}
// Enroll (or overwrite) a real name for a given embedding.
@Synchronized
fun addNamed(name: String, e: FloatArray) {
val v = l2normalize(e)
named.removeAll { it.first == name }
// Drop any auto entry whose embedding now equals this named one so the
// same voice is not also reported as an anonymous Sx id.
named.add(Pair(name, v))
}
/**
* Best cosine similarity of `e` against all enrolled speakers (0..1 scale,
* may be slightly noisy). Used by the rolling checker to tell "no idea
* whose voice this is" from "definitely the current speaker".
*/
@Synchronized
fun bestScore(e: FloatArray): Float {
val q = l2normalize(e)
var best = -1.0f
for ((_, emb) in named) best = maxOf(best, dot(q, emb))
for ((_, emb) in auto) best = maxOf(best, dot(q, emb))
return best
}
private fun match(
list: List<Pair<String, FloatArray>>,
e: FloatArray,
threshold: Float,
): String? {
if (list.isEmpty()) return null
val q = l2normalize(e)
var bestName: String? = null
var bestScore = -1.0f
for ((name, emb) in list) {
val s = dot(q, emb)
if (s > bestScore) {
bestScore = s
bestName = name
}
}
return if (bestScore >= threshold) bestName else null
}
private fun l2normalize(v: FloatArray): FloatArray {
var sum = 0.0f
for (x in v) sum += x * x
if (sum <= 0f) return v.copyOf()
val inv = 1.0f / sqrt(sum)
return FloatArray(v.size) { v[it] * inv }
}
private fun dot(a: FloatArray, b: FloatArray): Float {
var s = 0.0f
val n = minOf(a.size, b.size)
for (i in 0 until n) s += a[i] * b[i]
return s
}
}
// ---------------------------------------------------------------------------
// Singleton holder shared by the UI thread and the recording thread.
// ---------------------------------------------------------------------------
object SpeakerRecognition {
private var _extractor: SpeakerEmbeddingExtractor? = null
val extractor: SpeakerEmbeddingExtractor
get() = _extractor!!
val registry = SpeakerRegistry()
var autoCounter: Int = 0
private set
// autoCounter is touched from the recording thread (identifySpeaker) while
// resetSpeakers runs on the UI thread — keep them serialized.
@Synchronized
fun nextAutoLabel(): String = "S${autoCounter++}"
@Synchronized
fun resetSpeakers() {
registry.clear()
autoCounter = 0
}
// assetManager = null -> `model` is treated as an absolute file system path
fun initExtractor(assetManager: AssetManager?, model: String) {
synchronized(this) {
if (_extractor != null) return
Log.i(TAG, "Initializing speaker embedding extractor with $model")
_extractor = SpeakerEmbeddingExtractor(
assetManager = assetManager,
config = SpeakerEmbeddingExtractorConfig(
model = model,
numThreads = 2,
debug = false,
provider = "cpu",
)
)
}
}
// Compute one embedding from a complete utterance (float mono @ 16 kHz).
// Returns null when the utterance is too short for the model to consume.
// Serialized: the native extractor holds one session shared by the
// recording thread and the rolling-window checker thread.
@Synchronized
fun computeEmbedding(samples: FloatArray, sampleRate: Int): FloatArray? {
val ext = _extractor ?: return null
if (samples.isEmpty()) return null
val stream = ext.createStream()
stream.acceptWaveform(samples = samples, sampleRate = sampleRate)
stream.inputFinished()
val emb = if (ext.isReady(stream)) ext.compute(stream) else null
stream.release()
return emb
}
// Cosine similarity between two embeddings (L2-normalized internally),
// in [-1, 1]. Pure function, safe from any thread.
fun similarity(a: FloatArray, b: FloatArray): Float {
val n = minOf(a.size, b.size)
if (n == 0) return 0f
var dot = 0.0
var na = 0.0
var nb = 0.0
for (i in 0 until n) {
dot += a[i].toDouble() * b[i]
na += a[i].toDouble() * a[i]
nb += b[i].toDouble() * b[i]
}
if (na <= 0.0 || nb <= 0.0) return 0f
return (dot / (kotlin.math.sqrt(na) * kotlin.math.sqrt(nb))).toFloat()
}
private const val TAG = "sherpa-onnx-speaker"
}

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@ -0,0 +1,8 @@
package com.k2fsa.sherpa.onnx
data class SpeakerEmbeddingExtractorConfig(
val model: String = "",
var numThreads: Int = 1,
var debug: Boolean = false,
var provider: String = "cpu",
)

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@ -0,0 +1,30 @@
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xmlns:aapt="http://schemas.android.com/aapt"
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android:height="108dp"
android:viewportWidth="108"
android:viewportHeight="108">
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<aapt:attr name="android:fillColor">
<gradient
android:endX="85.84757"
android:endY="92.4963"
android:startX="42.9492"
android:startY="49.59793"
android:type="linear">
<item
android:color="#44000000"
android:offset="0.0" />
<item
android:color="#00000000"
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</gradient>
</aapt:attr>
</path>
<path
android:fillColor="#FFFFFF"
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android:strokeWidth="1"
android:strokeColor="#00000000" />
</vector>

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@ -0,0 +1,170 @@
<?xml version="1.0" encoding="utf-8"?>
<vector xmlns:android="http://schemas.android.com/apk/res/android"
android:width="108dp"
android:height="108dp"
android:viewportWidth="108"
android:viewportHeight="108">
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android:fillColor="#3DDC84"
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<path
android:fillColor="#00000000"
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android:strokeColor="#33FFFFFF" />
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</vector>

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<?xml version="1.0" encoding="utf-8"?>
<androidx.constraintlayout.widget.ConstraintLayout xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:app="http://schemas.android.com/apk/res-auto"
xmlns:tools="http://schemas.android.com/tools"
android:layout_width="match_parent"
android:layout_height="match_parent"
tools:context=".MainActivity">
<LinearLayout
android:layout_width="match_parent"
android:layout_height="match_parent"
android:gravity="center"
android:orientation="vertical">
<FrameLayout
android:layout_width="match_parent"
android:layout_height="0dp"
android:layout_weight="2.5">
<!-- subtitle dialog stream, one item per speaker line -->
<androidx.recyclerview.widget.RecyclerView
android:id="@+id/subtitle_list"
android:layout_width="match_parent"
android:layout_height="match_parent"
android:clipToPadding="false"
android:padding="24dp"
android:scrollbars="vertical"
android:visibility="gone" />
<!-- status / loading text, swapped with the subtitle list -->
<TextView
android:id="@+id/my_text"
android:layout_width="match_parent"
android:layout_height="match_parent"
android:padding="24dp"
android:scrollbars="vertical"
android:singleLine="false"
android:text="@string/hint"
android:gravity="bottom"
app:layout_constraintBottom_toBottomOf="parent"
app:layout_constraintEnd_toEndOf="parent"
app:layout_constraintStart_toStartOf="parent"
app:layout_constraintTop_toTopOf="parent" />
</FrameLayout>
<LinearLayout
android:layout_width="match_parent"
android:layout_height="wrap_content"
android:layout_weight="0.5"
android:gravity="center"
android:orientation="horizontal">
<Button
android:id="@+id/record_button"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:text="@string/start" />
<Button
android:id="@+id/name_speaker_button"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:layout_marginStart="12dp"
android:text="@string/name_speaker" />
<Button
android:id="@+id/clear_speakers_button"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:layout_marginStart="12dp"
android:text="@string/clear_speakers" />
</LinearLayout>
</LinearLayout>
</androidx.constraintlayout.widget.ConstraintLayout>

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<?xml version="1.0" encoding="utf-8"?>
<TextView xmlns:android="http://schemas.android.com/apk/res/android"
android:id="@+id/subtitle_text"
android:layout_width="match_parent"
android:layout_height="wrap_content"
android:paddingBottom="8dp"
android:textIsSelectable="true"
android:textSize="16sp" />

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<?xml version="1.0" encoding="utf-8"?>
<adaptive-icon xmlns:android="http://schemas.android.com/apk/res/android">
<background android:drawable="@drawable/ic_launcher_background" />
<foreground android:drawable="@drawable/ic_launcher_foreground" />
</adaptive-icon>

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<?xml version="1.0" encoding="utf-8"?>
<adaptive-icon xmlns:android="http://schemas.android.com/apk/res/android">
<background android:drawable="@drawable/ic_launcher_background" />
<foreground android:drawable="@drawable/ic_launcher_foreground" />
</adaptive-icon>

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<resources xmlns:tools="http://schemas.android.com/tools">
<!-- Base application theme. -->
<style name="Theme.SherpaOnnx2Pass" parent="Theme.MaterialComponents.DayNight.DarkActionBar">
<!-- Primary brand color. -->
<item name="colorPrimary">@color/purple_200</item>
<item name="colorPrimaryVariant">@color/purple_700</item>
<item name="colorOnPrimary">@color/black</item>
<!-- Secondary brand color. -->
<item name="colorSecondary">@color/teal_200</item>
<item name="colorSecondaryVariant">@color/teal_200</item>
<item name="colorOnSecondary">@color/black</item>
<!-- Status bar color. -->
<item name="android:statusBarColor">?attr/colorPrimaryVariant</item>
<!-- Customize your theme here. -->
</style>
</resources>

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@ -0,0 +1,10 @@
<?xml version="1.0" encoding="utf-8"?>
<resources>
<color name="purple_200">#FFBB86FC</color>
<color name="purple_500">#FF6200EE</color>
<color name="purple_700">#FF3700B3</color>
<color name="teal_200">#FF03DAC5</color>
<color name="teal_700">#FF018786</color>
<color name="black">#FF000000</color>
<color name="white">#FFFFFFFF</color>
</resources>

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@ -0,0 +1,15 @@
<resources>
<string name="app_name">ASR2pass </string>
<string name="hint">Click the Start button to play speech-to-text with Next-gen Kaldi.
\n
\n\n\n
The source code and pre-trained models are publicly available.
Please see https://github.com/k2-fsa/sherpa-onnx for details.
\n\n
Two-pass speech recognition with Next-gen Kaldi.
</string>
<string name="start">Start</string>
<string name="stop">Stop</string>
<string name="name_speaker">命名说话人</string>
<string name="clear_speakers">清除说话人</string>
</resources>

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@ -0,0 +1,16 @@
<resources xmlns:tools="http://schemas.android.com/tools">
<!-- Base application theme. -->
<style name="Theme.SherpaOnnx2Pass" parent="Theme.MaterialComponents.DayNight.DarkActionBar">
<!-- Primary brand color. -->
<item name="colorPrimary">@color/purple_500</item>
<item name="colorPrimaryVariant">@color/purple_700</item>
<item name="colorOnPrimary">@color/white</item>
<!-- Secondary brand color. -->
<item name="colorSecondary">@color/teal_200</item>
<item name="colorSecondaryVariant">@color/teal_700</item>
<item name="colorOnSecondary">@color/black</item>
<!-- Status bar color. -->
<item name="android:statusBarColor">?attr/colorPrimaryVariant</item>
<!-- Customize your theme here. -->
</style>
</resources>

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@ -0,0 +1,13 @@
<?xml version="1.0" encoding="utf-8"?><!--
Sample backup rules file; uncomment and customize as necessary.
See https://developer.android.com/guide/topics/data/autobackup
for details.
Note: This file is ignored for devices older that API 31
See https://developer.android.com/about/versions/12/backup-restore
-->
<full-backup-content>
<!--
<include domain="sharedpref" path="."/>
<exclude domain="sharedpref" path="device.xml"/>
-->
</full-backup-content>

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<?xml version="1.0" encoding="utf-8"?><!--
Sample data extraction rules file; uncomment and customize as necessary.
See https://developer.android.com/about/versions/12/backup-restore#xml-changes
for details.
-->
<data-extraction-rules>
<cloud-backup>
<!-- TODO: Use <include> and <exclude> to control what is backed up.
<include .../>
<exclude .../>
-->
</cloud-backup>
<!--
<device-transfer>
<include .../>
<exclude .../>
</device-transfer>
-->
</data-extraction-rules>

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package com.k2fsa.sherpa.onnx
import org.junit.Test
import org.junit.Assert.*
/**
* Example local unit test, which will execute on the development machine (host).
*
* See [testing documentation](http://d.android.com/tools/testing).
*/
class ExampleUnitTest {
@Test
fun addition_isCorrect() {
assertEquals(4, 2 + 2)
}
}

6
build.gradle Normal file
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// Top-level build file where you can add configuration options common to all sub-projects/modules.
plugins {
id 'com.android.application' version '7.3.1' apply false
id 'com.android.library' version '7.3.1' apply false
id 'org.jetbrains.kotlin.android' version '1.7.20' apply false
}

25
gradle.properties Normal file
View File

@ -0,0 +1,25 @@
# Project-wide Gradle settings.
# IDE (e.g. Android Studio) users:
# Gradle settings configured through the IDE *will override*
# any settings specified in this file.
# For more details on how to configure your build environment visit
# http://www.gradle.org/docs/current/userguide/build_environment.html
# Specifies the JVM arguments used for the daemon process.
# The setting is particularly useful for tweaking memory settings.
org.gradle.jvmargs=-Xmx4096m -XX:MaxMetaspaceSize=1024m -Dfile.encoding=UTF-8
# When configured, Gradle will run in incubating parallel mode.
# This option should only be used with decoupled projects. More details, visit
# http://www.gradle.org/docs/current/userguide/multi_project_builds.html#sec:decoupled_projects
# org.gradle.parallel=true
# AndroidX package structure to make it clearer which packages are bundled with the
# Android operating system, and which are packaged with your app's APK
# https://developer.android.com/topic/libraries/support-library/androidx-rn
android.useAndroidX=true
# Kotlin code style for this project: "official" or "obsolete":
kotlin.code.style=official
# Enables namespacing of each library's R class so that its R class includes only the
# resources declared in the library itself and none from the library's dependencies,
# thereby reducing the size of the R class for that library
android.nonTransitiveRClass=true
# Kotlin 编译守护进程内存(默认继承较少,单独指定)
kotlin.daemon.jvmargs=-Xmx2048m

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gradle/wrapper/gradle-wrapper.jar vendored Normal file

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#Sun Sep 10 18:03:03 CST 2023
distributionBase=GRADLE_USER_HOME
distributionUrl=https\://services.gradle.org/distributions/gradle-8.2-bin.zip
distributionPath=wrapper/dists
zipStorePath=wrapper/dists
zipStoreBase=GRADLE_USER_HOME

185
gradlew vendored Normal file
View File

@ -0,0 +1,185 @@
#!/usr/bin/env sh
#
# Copyright 2015 the original author or authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
##############################################################################
##
## Gradle start up script for UN*X
##
##############################################################################
# Attempt to set APP_HOME
# Resolve links: $0 may be a link
PRG="$0"
# Need this for relative symlinks.
while [ -h "$PRG" ] ; do
ls=`ls -ld "$PRG"`
link=`expr "$ls" : '.*-> \(.*\)$'`
if expr "$link" : '/.*' > /dev/null; then
PRG="$link"
else
PRG=`dirname "$PRG"`"/$link"
fi
done
SAVED="`pwd`"
cd "`dirname \"$PRG\"`/" >/dev/null
APP_HOME="`pwd -P`"
cd "$SAVED" >/dev/null
APP_NAME="Gradle"
APP_BASE_NAME=`basename "$0"`
# Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.
DEFAULT_JVM_OPTS='"-Xmx64m" "-Xms64m"'
# Use the maximum available, or set MAX_FD != -1 to use that value.
MAX_FD="maximum"
warn () {
echo "$*"
}
die () {
echo
echo "$*"
echo
exit 1
}
# OS specific support (must be 'true' or 'false').
cygwin=false
msys=false
darwin=false
nonstop=false
case "`uname`" in
CYGWIN* )
cygwin=true
;;
Darwin* )
darwin=true
;;
MINGW* )
msys=true
;;
NONSTOP* )
nonstop=true
;;
esac
CLASSPATH=$APP_HOME/gradle/wrapper/gradle-wrapper.jar
# Determine the Java command to use to start the JVM.
if [ -n "$JAVA_HOME" ] ; then
if [ -x "$JAVA_HOME/jre/sh/java" ] ; then
# IBM's JDK on AIX uses strange locations for the executables
JAVACMD="$JAVA_HOME/jre/sh/java"
else
JAVACMD="$JAVA_HOME/bin/java"
fi
if [ ! -x "$JAVACMD" ] ; then
die "ERROR: JAVA_HOME is set to an invalid directory: $JAVA_HOME
Please set the JAVA_HOME variable in your environment to match the
location of your Java installation."
fi
else
JAVACMD="java"
which java >/dev/null 2>&1 || die "ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
Please set the JAVA_HOME variable in your environment to match the
location of your Java installation."
fi
# Increase the maximum file descriptors if we can.
if [ "$cygwin" = "false" -a "$darwin" = "false" -a "$nonstop" = "false" ] ; then
MAX_FD_LIMIT=`ulimit -H -n`
if [ $? -eq 0 ] ; then
if [ "$MAX_FD" = "maximum" -o "$MAX_FD" = "max" ] ; then
MAX_FD="$MAX_FD_LIMIT"
fi
ulimit -n $MAX_FD
if [ $? -ne 0 ] ; then
warn "Could not set maximum file descriptor limit: $MAX_FD"
fi
else
warn "Could not query maximum file descriptor limit: $MAX_FD_LIMIT"
fi
fi
# For Darwin, add options to specify how the application appears in the dock
if $darwin; then
GRADLE_OPTS="$GRADLE_OPTS \"-Xdock:name=$APP_NAME\" \"-Xdock:icon=$APP_HOME/media/gradle.icns\""
fi
# For Cygwin or MSYS, switch paths to Windows format before running java
if [ "$cygwin" = "true" -o "$msys" = "true" ] ; then
APP_HOME=`cygpath --path --mixed "$APP_HOME"`
CLASSPATH=`cygpath --path --mixed "$CLASSPATH"`
JAVACMD=`cygpath --unix "$JAVACMD"`
# We build the pattern for arguments to be converted via cygpath
ROOTDIRSRAW=`find -L / -maxdepth 1 -mindepth 1 -type d 2>/dev/null`
SEP=""
for dir in $ROOTDIRSRAW ; do
ROOTDIRS="$ROOTDIRS$SEP$dir"
SEP="|"
done
OURCYGPATTERN="(^($ROOTDIRS))"
# Add a user-defined pattern to the cygpath arguments
if [ "$GRADLE_CYGPATTERN" != "" ] ; then
OURCYGPATTERN="$OURCYGPATTERN|($GRADLE_CYGPATTERN)"
fi
# Now convert the arguments - kludge to limit ourselves to /bin/sh
i=0
for arg in "$@" ; do
CHECK=`echo "$arg"|egrep -c "$OURCYGPATTERN" -`
CHECK2=`echo "$arg"|egrep -c "^-"` ### Determine if an option
if [ $CHECK -ne 0 ] && [ $CHECK2 -eq 0 ] ; then ### Added a condition
eval `echo args$i`=`cygpath --path --ignore --mixed "$arg"`
else
eval `echo args$i`="\"$arg\""
fi
i=`expr $i + 1`
done
case $i in
0) set -- ;;
1) set -- "$args0" ;;
2) set -- "$args0" "$args1" ;;
3) set -- "$args0" "$args1" "$args2" ;;
4) set -- "$args0" "$args1" "$args2" "$args3" ;;
5) set -- "$args0" "$args1" "$args2" "$args3" "$args4" ;;
6) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" ;;
7) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" ;;
8) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" ;;
9) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" "$args8" ;;
esac
fi
# Escape application args
save () {
for i do printf %s\\n "$i" | sed "s/'/'\\\\''/g;1s/^/'/;\$s/\$/' \\\\/" ; done
echo " "
}
APP_ARGS=`save "$@"`
# Collect all arguments for the java command, following the shell quoting and substitution rules
eval set -- $DEFAULT_JVM_OPTS $JAVA_OPTS $GRADLE_OPTS "\"-Dorg.gradle.appname=$APP_BASE_NAME\"" -classpath "\"$CLASSPATH\"" org.gradle.wrapper.GradleWrapperMain "$APP_ARGS"
exec "$JAVACMD" "$@"

89
gradlew.bat vendored Normal file
View File

@ -0,0 +1,89 @@
@rem
@rem Copyright 2015 the original author or authors.
@rem
@rem Licensed under the Apache License, Version 2.0 (the "License");
@rem you may not use this file except in compliance with the License.
@rem You may obtain a copy of the License at
@rem
@rem https://www.apache.org/licenses/LICENSE-2.0
@rem
@rem Unless required by applicable law or agreed to in writing, software
@rem distributed under the License is distributed on an "AS IS" BASIS,
@rem WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
@rem See the License for the specific language governing permissions and
@rem limitations under the License.
@rem
@if "%DEBUG%" == "" @echo off
@rem ##########################################################################
@rem
@rem Gradle startup script for Windows
@rem
@rem ##########################################################################
@rem Set local scope for the variables with windows NT shell
if "%OS%"=="Windows_NT" setlocal
set DIRNAME=%~dp0
if "%DIRNAME%" == "" set DIRNAME=.
set APP_BASE_NAME=%~n0
set APP_HOME=%DIRNAME%
@rem Resolve any "." and ".." in APP_HOME to make it shorter.
for %%i in ("%APP_HOME%") do set APP_HOME=%%~fi
@rem Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.
set DEFAULT_JVM_OPTS="-Xmx64m" "-Xms64m"
@rem Find java.exe
if defined JAVA_HOME goto findJavaFromJavaHome
set JAVA_EXE=java.exe
%JAVA_EXE% -version >NUL 2>&1
if "%ERRORLEVEL%" == "0" goto execute
echo.
echo ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
echo.
echo Please set the JAVA_HOME variable in your environment to match the
echo location of your Java installation.
goto fail
:findJavaFromJavaHome
set JAVA_HOME=%JAVA_HOME:"=%
set JAVA_EXE=%JAVA_HOME%/bin/java.exe
if exist "%JAVA_EXE%" goto execute
echo.
echo ERROR: JAVA_HOME is set to an invalid directory: %JAVA_HOME%
echo.
echo Please set the JAVA_HOME variable in your environment to match the
echo location of your Java installation.
goto fail
:execute
@rem Setup the command line
set CLASSPATH=%APP_HOME%\gradle\wrapper\gradle-wrapper.jar
@rem Execute Gradle
"%JAVA_EXE%" %DEFAULT_JVM_OPTS% %JAVA_OPTS% %GRADLE_OPTS% "-Dorg.gradle.appname=%APP_BASE_NAME%" -classpath "%CLASSPATH%" org.gradle.wrapper.GradleWrapperMain %*
:end
@rem End local scope for the variables with windows NT shell
if "%ERRORLEVEL%"=="0" goto mainEnd
:fail
rem Set variable GRADLE_EXIT_CONSOLE if you need the _script_ return code instead of
rem the _cmd.exe /c_ return code!
if not "" == "%GRADLE_EXIT_CONSOLE%" exit 1
exit /b 1
:mainEnd
if "%OS%"=="Windows_NT" endlocal
:omega

16
settings.gradle Normal file
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@ -0,0 +1,16 @@
pluginManagement {
repositories {
gradlePluginPortal()
google()
mavenCentral()
}
}
dependencyResolutionManagement {
repositoriesMode.set(RepositoriesMode.FAIL_ON_PROJECT_REPOS)
repositories {
google()
mavenCentral()
}
}
rootProject.name = "SherpaOnnx2Pass"
include ':app'