Add Swift API for spoken language identification. (#696)
This commit is contained in:
3
.github/scripts/test-swift.sh
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3
.github/scripts/test-swift.sh
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@@ -7,6 +7,9 @@ echo "pwd: $PWD"
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cd swift-api-examples
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ls -lh
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./run-spoken-language-identification.sh
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rm -rf sherpa-onnx-whisper*
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mkdir -p /Users/fangjun/Desktop
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pushd /Users/fangjun/Desktop
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curl -SL -O https://huggingface.co/csukuangfj/test-data/resolve/main/Obama.wav
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1
swift-api-examples/.gitignore
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1
swift-api-examples/.gitignore
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@@ -1,6 +1,7 @@
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decode-file
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decode-file-non-streaming
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generate-subtitles
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spoken-language-identification
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tts
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vits-vctk
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sherpa-onnx-paraformer-zh-2023-09-14
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@@ -713,3 +713,86 @@ class SherpaOnnxOfflineTtsWrapper {
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return SherpaOnnxGeneratedAudioWrapper(audio: audio)
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}
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}
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// spoken language identification
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func sherpaOnnxSpokenLanguageIdentificationWhisperConfig(
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encoder: String,
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decoder: String,
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tailPaddings: Int = -1
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) -> SherpaOnnxSpokenLanguageIdentificationWhisperConfig {
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return SherpaOnnxSpokenLanguageIdentificationWhisperConfig(
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encoder: toCPointer(encoder),
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decoder: toCPointer(decoder),
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tail_paddings: Int32(tailPaddings))
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}
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func sherpaOnnxSpokenLanguageIdentificationConfig(
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whisper: SherpaOnnxSpokenLanguageIdentificationWhisperConfig,
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numThreads: Int = 1,
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debug: Int = 0,
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provider: String = "cpu"
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) -> SherpaOnnxSpokenLanguageIdentificationConfig {
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return SherpaOnnxSpokenLanguageIdentificationConfig(
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whisper: whisper,
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num_threads: Int32(numThreads),
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debug: Int32(debug),
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provider: toCPointer(provider))
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}
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class SherpaOnnxSpokenLanguageIdentificationResultWrapper {
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/// A pointer to the underlying counterpart in C
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let result: UnsafePointer<SherpaOnnxSpokenLanguageIdentificationResult>!
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/// Return the detected language.
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/// en for English
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/// zh for Chinese
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/// es for Spanish
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/// de for German
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/// etc.
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var lang: String {
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return String(cString: result.pointee.lang)
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}
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init(result: UnsafePointer<SherpaOnnxSpokenLanguageIdentificationResult>!) {
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self.result = result
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}
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deinit {
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if let result {
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SherpaOnnxDestroySpokenLanguageIdentificationResult(result)
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}
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}
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}
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class SherpaOnnxSpokenLanguageIdentificationWrapper {
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/// A pointer to the underlying counterpart in C
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let slid: OpaquePointer!
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init(
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config: UnsafePointer<SherpaOnnxSpokenLanguageIdentificationConfig>!
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) {
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slid = SherpaOnnxCreateSpokenLanguageIdentification(config)
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}
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deinit {
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if let slid {
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SherpaOnnxDestroySpokenLanguageIdentification(slid)
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}
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}
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func decode(samples: [Float], sampleRate: Int = 16000)
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-> SherpaOnnxSpokenLanguageIdentificationResultWrapper
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{
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let stream: OpaquePointer! = SherpaOnnxSpokenLanguageIdentificationCreateOfflineStream(slid)
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AcceptWaveformOffline(stream, Int32(sampleRate), samples, Int32(samples.count))
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let result: UnsafePointer<SherpaOnnxSpokenLanguageIdentificationResult>? =
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SherpaOnnxSpokenLanguageIdentificationCompute(
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slid,
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stream)
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DestroyOfflineStream(stream)
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return SherpaOnnxSpokenLanguageIdentificationResultWrapper(result: result)
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}
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}
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36
swift-api-examples/run-spoken-language-identification.sh
Executable file
36
swift-api-examples/run-spoken-language-identification.sh
Executable file
@@ -0,0 +1,36 @@
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#!/usr/bin/env bash
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set -ex
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if [ ! -d ../build-swift-macos ]; then
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echo "Please run ../build-swift-macos.sh first!"
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exit 1
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fi
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if [ ! -d ./sherpa-onnx-whisper-tiny ]; then
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echo "Download a pre-trained model for testing."
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curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-whisper-tiny.tar.bz2
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tar xvf sherpa-onnx-whisper-tiny.tar.bz2
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rm sherpa-onnx-whisper-tiny.tar.bz2
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fi
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if [ ! -e ./spoken-language-identification ]; then
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# Note: We use -lc++ to link against libc++ instead of libstdc++
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swiftc \
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-lc++ \
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-I ../build-swift-macos/install/include \
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-import-objc-header ./SherpaOnnx-Bridging-Header.h \
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./spoken-language-identification.swift ./SherpaOnnx.swift \
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-L ../build-swift-macos/install/lib/ \
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-l sherpa-onnx \
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-l onnxruntime \
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-o spoken-language-identification
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strip spoken-language-identification
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else
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echo "./spoken-language-identification exists - skip building"
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fi
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export DYLD_LIBRARY_PATH=$PWD/../build-swift-macos/install/lib:$DYLD_LIBRARY_PATH
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./spoken-language-identification
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57
swift-api-examples/spoken-language-identification.swift
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57
swift-api-examples/spoken-language-identification.swift
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@@ -0,0 +1,57 @@
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import AVFoundation
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extension AudioBuffer {
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func array() -> [Float] {
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return Array(UnsafeBufferPointer(self))
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}
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}
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extension AVAudioPCMBuffer {
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func array() -> [Float] {
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return self.audioBufferList.pointee.mBuffers.array()
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}
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}
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func run() {
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let encoder = "./sherpa-onnx-whisper-tiny/tiny-encoder.int8.onnx"
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let decoder = "./sherpa-onnx-whisper-tiny/tiny-decoder.int8.onnx"
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let whisperConfig = sherpaOnnxSpokenLanguageIdentificationWhisperConfig(
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encoder: encoder,
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decoder: decoder
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)
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var config = sherpaOnnxSpokenLanguageIdentificationConfig(
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whisper: whisperConfig,
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numThreads: 1,
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debug: 1,
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provider: "cpu"
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)
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let filePath = "./sherpa-onnx-whisper-tiny/test_wavs/0.wav"
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let slid = SherpaOnnxSpokenLanguageIdentificationWrapper(config: &config)
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let fileURL: NSURL = NSURL(fileURLWithPath: filePath)
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let audioFile = try! AVAudioFile(forReading: fileURL as URL)
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let audioFormat = audioFile.processingFormat
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assert(audioFormat.sampleRate == 16000)
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assert(audioFormat.channelCount == 1)
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assert(audioFormat.commonFormat == AVAudioCommonFormat.pcmFormatFloat32)
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let audioFrameCount = UInt32(audioFile.length)
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let audioFileBuffer = AVAudioPCMBuffer(pcmFormat: audioFormat, frameCapacity: audioFrameCount)
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try! audioFile.read(into: audioFileBuffer!)
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let array: [Float]! = audioFileBuffer?.array()
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let result = slid.decode(samples: array)
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print("\nDetectedllanguage is:\n\(result.lang)")
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}
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@main
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struct App {
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static func main() {
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run()
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}
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}
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