Add two-pass speech recognition Android/iOS demo (#304)

This commit is contained in:
Fangjun Kuang
2023-09-12 15:40:16 +08:00
committed by GitHub
parent 8982984ea2
commit debab7c091
97 changed files with 3546 additions and 57 deletions

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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: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
import android.Manifest
import android.content.pm.PackageManager
import android.media.AudioFormat
import android.media.AudioRecord
import android.media.MediaRecorder
import android.os.Bundle
import android.text.method.ScrollingMovementMethod
import android.util.Log
import android.widget.Button
import android.widget.TextView
import androidx.appcompat.app.AppCompatActivity
import androidx.core.app.ActivityCompat
import kotlin.concurrent.thread
private const val TAG = "sherpa-onnx"
private const val REQUEST_RECORD_AUDIO_PERMISSION = 200
class MainActivity : AppCompatActivity() {
private val permissions: Array<String> = arrayOf(Manifest.permission.RECORD_AUDIO)
private lateinit var onlineRecognizer: SherpaOnnx
private lateinit var offlineRecognizer: SherpaOnnxOffline
private var audioRecord: AudioRecord? = null
private lateinit var recordButton: Button
private lateinit var textView: TextView
private var recordingThread: Thread? = null
private val audioSource = MediaRecorder.AudioSource.MIC
private val sampleRateInHz = 16000
private val channelConfig = AudioFormat.CHANNEL_IN_MONO
private var samplesBuffer = arrayListOf<FloatArray>()
// Note: We don't use AudioFormat.ENCODING_PCM_FLOAT
// since the AudioRecord.read(float[]) needs API level >= 23
// but we are targeting API level >= 21
private val audioFormat = AudioFormat.ENCODING_PCM_16BIT
private var idx: Int = 0
private var lastText: String = ""
@Volatile
private var isRecording: Boolean = false
override fun onRequestPermissionsResult(
requestCode: Int, permissions: Array<String>, grantResults: IntArray
) {
super.onRequestPermissionsResult(requestCode, permissions, grantResults)
val permissionToRecordAccepted = if (requestCode == REQUEST_RECORD_AUDIO_PERMISSION) {
grantResults[0] == PackageManager.PERMISSION_GRANTED
} else {
false
}
if (!permissionToRecordAccepted) {
Log.e(TAG, "Audio record is disallowed")
finish()
}
Log.i(TAG, "Audio record is permitted")
}
override fun onCreate(savedInstanceState: Bundle?) {
super.onCreate(savedInstanceState)
setContentView(R.layout.activity_main)
ActivityCompat.requestPermissions(this, permissions, REQUEST_RECORD_AUDIO_PERMISSION)
Log.i(TAG, "Start to initialize first-pass recognizer")
initOnlineRecognizer()
Log.i(TAG, "Finished initializing first-pass recognizer")
Log.i(TAG, "Start to initialize second-pass recognizer")
initOfflineRecognizer()
Log.i(TAG, "Finished initializing second-pass recognizer")
recordButton = findViewById(R.id.record_button)
recordButton.setOnClickListener { onclick() }
textView = findViewById(R.id.my_text)
textView.movementMethod = ScrollingMovementMethod()
}
private fun onclick() {
if (!isRecording) {
val ret = initMicrophone()
if (!ret) {
Log.e(TAG, "Failed to initialize microphone")
return
}
Log.i(TAG, "state: ${audioRecord?.state}")
audioRecord!!.startRecording()
recordButton.setText(R.string.stop)
isRecording = true
onlineRecognizer.reset(true)
samplesBuffer.clear()
textView.text = ""
lastText = ""
idx = 0
recordingThread = thread(true) {
processSamples()
}
Log.i(TAG, "Started recording")
} else {
isRecording = false
audioRecord!!.stop()
audioRecord!!.release()
audioRecord = null
recordButton.setText(R.string.start)
Log.i(TAG, "Stopped recording")
}
}
private fun processSamples() {
Log.i(TAG, "processing samples")
val interval = 0.1 // i.e., 100 ms
val bufferSize = (interval * sampleRateInHz).toInt() // in samples
val buffer = ShortArray(bufferSize)
while (isRecording) {
val ret = audioRecord?.read(buffer, 0, buffer.size)
if (ret != null && ret > 0) {
val samples = FloatArray(ret) { buffer[it] / 32768.0f }
samplesBuffer.add(samples)
onlineRecognizer.acceptWaveform(samples, sampleRate = sampleRateInHz)
while (onlineRecognizer.isReady()) {
onlineRecognizer.decode()
}
val isEndpoint = onlineRecognizer.isEndpoint()
var textToDisplay = lastText
var text = onlineRecognizer.text
if (text.isNotBlank()) {
if (lastText.isBlank()) {
// textView.text = "${idx}: ${text}"
textToDisplay = "${idx}: ${text}"
} else {
textToDisplay = "${lastText}\n${idx}: ${text}"
}
}
if (isEndpoint) {
onlineRecognizer.reset()
if (text.isNotBlank()) {
text = runSecondPass()
lastText = "${lastText}\n${idx}: ${text}"
idx += 1
} else {
samplesBuffer.clear()
}
}
runOnUiThread {
textView.text = textToDisplay.lowercase()
}
}
}
}
private fun initMicrophone(): Boolean {
if (ActivityCompat.checkSelfPermission(
this, Manifest.permission.RECORD_AUDIO
) != PackageManager.PERMISSION_GRANTED
) {
ActivityCompat.requestPermissions(this, permissions, REQUEST_RECORD_AUDIO_PERMISSION)
return false
}
val numBytes = AudioRecord.getMinBufferSize(sampleRateInHz, channelConfig, audioFormat)
Log.i(
TAG, "buffer size in milliseconds: ${numBytes * 1000.0f / sampleRateInHz}"
)
audioRecord = AudioRecord(
audioSource,
sampleRateInHz,
channelConfig,
audioFormat,
numBytes * 2 // a sample has two bytes as we are using 16-bit PCM
)
return true
}
private fun initOnlineRecognizer() {
// Please change getModelConfig() to add new models
// See https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html
// for a list of available models
val firstType = 1
println("Select model type ${firstType} for the first pass")
val config = OnlineRecognizerConfig(
featConfig = getFeatureConfig(sampleRate = sampleRateInHz, featureDim = 80),
modelConfig = getModelConfig(type = firstType)!!,
endpointConfig = getEndpointConfig(),
enableEndpoint = true,
)
onlineRecognizer = SherpaOnnx(
assetManager = application.assets,
config = config,
)
}
private fun initOfflineRecognizer() {
// Please change getOfflineModelConfig() to add new models
// See https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html
// for a list of available models
val secondType = 1
println("Select model type ${secondType} for the second pass")
val config = OfflineRecognizerConfig(
featConfig = getFeatureConfig(sampleRate = sampleRateInHz, featureDim = 80),
modelConfig = getOfflineModelConfig(type = secondType)!!,
)
offlineRecognizer = SherpaOnnxOffline(
assetManager = application.assets,
config = config,
)
}
private fun runSecondPass(): String {
var totalSamples = 0
for (a in samplesBuffer) {
totalSamples += a.size
}
var i = 0
val samples = FloatArray(totalSamples)
// todo(fangjun): Make it more efficient
for (a in samplesBuffer) {
for (s in a) {
samples[i] = s
i += 1
}
}
val n = maxOf(0, samples.size - 8000)
samplesBuffer.clear()
samplesBuffer.add(samples.sliceArray(n..samples.size-1))
return offlineRecognizer.decode(samples.sliceArray(0..n), sampleRateInHz)
}
}

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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, 2.0f, 0.0f),
var rule2: EndpointRule = EndpointRule(true, 1.2f, 0.0f),
var rule3: EndpointRule = EndpointRule(false, 0.0f, 20.0f)
)
data class OnlineTransducerModelConfig(
var encoder: String = "",
var decoder: String = "",
var joiner: String = "",
)
data class OnlineParaformerModelConfig(
var encoder: String = "",
var decoder: String = "",
)
data class OnlineModelConfig(
var transducer: OnlineTransducerModelConfig = OnlineTransducerModelConfig(),
var paraformer: OnlineParaformerModelConfig = OnlineParaformerModelConfig(),
var tokens: String,
var numThreads: Int = 1,
var debug: Boolean = false,
var provider: String = "cpu",
var modelType: String = "",
)
data class OnlineLMConfig(
var model: String = "",
var scale: Float = 0.5f,
)
data class FeatureConfig(
var sampleRate: Int = 16000,
var featureDim: Int = 80,
)
data class OnlineRecognizerConfig(
var featConfig: FeatureConfig = FeatureConfig(),
var modelConfig: OnlineModelConfig,
var lmConfig: OnlineLMConfig = OnlineLMConfig(),
var endpointConfig: EndpointConfig = EndpointConfig(),
var enableEndpoint: Boolean = true,
var decodingMethod: String = "greedy_search",
var maxActivePaths: Int = 4,
)
data class OfflineTransducerModelConfig(
var encoder: String = "",
var decoder: String = "",
var joiner: String = "",
)
data class OfflineParaformerModelConfig(
var model: String = "",
)
data class OfflineWhisperModelConfig(
var encoder: String = "",
var decoder: String = "",
)
data class OfflineModelConfig(
var transducer: OfflineTransducerModelConfig = OfflineTransducerModelConfig(),
var paraformer: OfflineParaformerModelConfig = OfflineParaformerModelConfig(),
var whisper: OfflineWhisperModelConfig = OfflineWhisperModelConfig(),
var numThreads: Int = 1,
var debug: Boolean = false,
var provider: String = "cpu",
var modelType: String = "",
var tokens: String,
)
data class OfflineRecognizerConfig(
var featConfig: FeatureConfig = FeatureConfig(),
var modelConfig: OfflineModelConfig,
// var lmConfig: OfflineLMConfig(), // TODO(fangjun): enable it
var decodingMethod: String = "greedy_search",
var maxActivePaths: Int = 4,
)
class SherpaOnnx(
assetManager: AssetManager? = null,
var config: OnlineRecognizerConfig,
) {
private val ptr: Long
init {
if (assetManager != null) {
ptr = new(assetManager, config)
} else {
ptr = newFromFile(config)
}
}
protected fun finalize() {
delete(ptr)
}
fun acceptWaveform(samples: FloatArray, sampleRate: Int) =
acceptWaveform(ptr, samples, sampleRate)
fun inputFinished() = inputFinished(ptr)
fun reset(recreate: Boolean = false) = reset(ptr, recreate = recreate)
fun decode() = decode(ptr)
fun isEndpoint(): Boolean = isEndpoint(ptr)
fun isReady(): Boolean = isReady(ptr)
val text: String
get() = getText(ptr)
private external fun delete(ptr: Long)
private external fun new(
assetManager: AssetManager,
config: OnlineRecognizerConfig,
): Long
private external fun newFromFile(
config: OnlineRecognizerConfig,
): Long
private external fun acceptWaveform(ptr: Long, samples: FloatArray, sampleRate: Int)
private external fun inputFinished(ptr: Long)
private external fun getText(ptr: Long): String
private external fun reset(ptr: Long, recreate: Boolean)
private external fun decode(ptr: Long)
private external fun isEndpoint(ptr: Long): Boolean
private external fun isReady(ptr: Long): Boolean
companion object {
init {
System.loadLibrary("sherpa-onnx-jni")
}
}
}
class SherpaOnnxOffline(
assetManager: AssetManager? = null,
var config: OfflineRecognizerConfig,
) {
private val ptr: Long
init {
if (assetManager != null) {
ptr = new(assetManager, config)
} else {
ptr = newFromFile(config)
}
}
protected fun finalize() {
delete(ptr)
}
fun decode(samples: FloatArray, sampleRate: Int) = decode(ptr, samples, sampleRate)
private external fun delete(ptr: Long)
private external fun new(
assetManager: AssetManager,
config: OfflineRecognizerConfig,
): Long
private external fun newFromFile(
config: OfflineRecognizerConfig,
): Long
private external fun decode(ptr: Long, samples: FloatArray, sampleRate: Int): String
companion object {
init {
System.loadLibrary("sherpa-onnx-jni")
}
}
}
fun getFeatureConfig(sampleRate: Int, featureDim: Int): FeatureConfig {
return FeatureConfig(sampleRate = sampleRate, featureDim = featureDim)
}
/*
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 - csukuangfj/sherpa-onnx-streaming-zipformer-zh-14M-2023-02-23 (Chinese)
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html#sherpa-onnx-streaming-zipformer-zh-14m-2023-02-23
encoder/joiner int8, decoder float32
1 - csukuangfj/sherpa-onnx-streaming-zipformer-en-20M-2023-02-17 (English)
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html#csukuangfj-sherpa-onnx-streaming-zipformer-en-20m-2023-02-17-english
encoder/joiner int8, decoder fp32
*/
fun getModelConfig(type: Int): OnlineModelConfig? {
when (type) {
0 -> {
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",
)
}
1 -> {
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",
)
}
}
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 = "$modelDir/with-state-epoch-99-avg-1.int8.onnx",
scale = 0.5f,
)
}
}
return OnlineLMConfig()
}
// for English models, use a small value for rule2.minTrailingSilence, e.g., 0.8
fun getEndpointConfig(): EndpointConfig {
return EndpointConfig(
rule1 = EndpointRule(false, 2.4f, 0.0f),
rule2 = EndpointRule(true, 0.8f, 0.0f),
rule3 = EndpointRule(false, 0.0f, 20.0f)
)
}
/*
Please see
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html
for a list of pre-trained models.
We only add a few here. Please change the following code
to add your own. (It should be straightforward to add a new model
by following the code)
@param type
0 - csukuangfj/sherpa-onnx-paraformer-zh-2023-03-28 (Chinese)
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/offline-paraformer/paraformer-models.html#csukuangfj-sherpa-onnx-paraformer-zh-2023-03-28-chinese
int8
1 - icefall-asr-multidataset-pruned_transducer_stateless7-2023-05-04 (English)
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/offline-transducer/zipformer-transducer-models.html#icefall-asr-multidataset-pruned-transducer-stateless7-2023-05-04-english
encoder int8, decoder/joiner float32
2 - sherpa-onnx-whisper-tiny.en
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/whisper/tiny.en.html#tiny-en
encoder int8, decoder int8
3 - sherpa-onnx-whisper-base.en
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/whisper/tiny.en.html#tiny-en
encoder int8, decoder int8
4 - pkufool/icefall-asr-zipformer-wenetspeech-20230615 (Chinese)
https://k2-fsa.github.io/sherpa/onnx/pretrained_models/offline-transducer/zipformer-transducer-models.html#pkufool-icefall-asr-zipformer-wenetspeech-20230615-chinese
encoder/joiner int8, decoder fp32
*/
fun getOfflineModelConfig(type: Int): OfflineModelConfig? {
when (type) {
0 -> {
val modelDir = "sherpa-onnx-paraformer-zh-2023-03-28"
return OfflineModelConfig(
paraformer = OfflineParaformerModelConfig(
model = "$modelDir/model.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "paraformer",
)
}
1 -> {
val modelDir = "icefall-asr-multidataset-pruned_transducer_stateless7-2023-05-04"
return OfflineModelConfig(
transducer = OfflineTransducerModelConfig(
encoder = "$modelDir/encoder-epoch-30-avg-4.int8.onnx",
decoder = "$modelDir/decoder-epoch-30-avg-4.onnx",
joiner = "$modelDir/joiner-epoch-30-avg-4.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer",
)
}
2 -> {
val modelDir = "sherpa-onnx-whisper-tiny.en"
return OfflineModelConfig(
whisper = OfflineWhisperModelConfig(
encoder = "$modelDir/tiny.en-encoder.int8.onnx",
decoder = "$modelDir/tiny.en-decoder.int8.onnx",
),
tokens = "$modelDir/tiny.en-tokens.txt",
modelType = "whisper",
)
}
3 -> {
val modelDir = "sherpa-onnx-whisper-base.en"
return OfflineModelConfig(
whisper = OfflineWhisperModelConfig(
encoder = "$modelDir/base.en-encoder.int8.onnx",
decoder = "$modelDir/base.en-decoder.int8.onnx",
),
tokens = "$modelDir/base.en-tokens.txt",
modelType = "whisper",
)
}
4 -> {
val modelDir = "icefall-asr-zipformer-wenetspeech-20230615"
return OfflineModelConfig(
transducer = OfflineTransducerModelConfig(
encoder = "$modelDir/encoder-epoch-12-avg-4.int8.onnx",
decoder = "$modelDir/decoder-epoch-12-avg-4.onnx",
joiner = "$modelDir/joiner-epoch-12-avg-4.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
modelType = "zipformer",
)
}
}
return null
}

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../../../../../../../../../SherpaOnnx/app/src/main/java/com/k2fsa/sherpa/onnx/WaveReader.kt

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<vector xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:aapt="http://schemas.android.com/aapt"
android:width="108dp"
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"
android:offset="1.0" />
</gradient>
</aapt:attr>
</path>
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android:strokeWidth="1"
android:strokeColor="#00000000" />
</vector>

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<?xml version="1.0" encoding="utf-8"?>
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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">
<TextView
android:id="@+id/my_text"
android:layout_width="match_parent"
android:layout_height="match_parent"
android:layout_weight="2.5"
android:padding="24dp"
android:scrollbars="vertical"
android:singleLine="false"
android:text="@string/hint"
app:layout_constraintBottom_toBottomOf="parent"
app:layout_constraintEnd_toEndOf="parent"
app:layout_constraintStart_toStartOf="parent"
android:gravity="bottom"
app:layout_constraintTop_toTopOf="parent" />
<Button
android:id="@+id/record_button"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:layout_weight="0.5"
android:text="@string/start" />
</LinearLayout>
</androidx.constraintlayout.widget.ConstraintLayout>

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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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<?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 +1,13 @@
<resources>
<string name="app_name">ASR with Next-gen Kaldi</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>
</resources>

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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_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>

View File

@@ -0,0 +1,19 @@
<?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)
}
}