Add C API for spoken language identification. (#695)
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@@ -7,8 +7,11 @@ target_link_libraries(decode-file-c-api sherpa-onnx-c-api cargs)
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add_executable(offline-tts-c-api offline-tts-c-api.c)
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target_link_libraries(offline-tts-c-api sherpa-onnx-c-api cargs)
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add_executable(spoken-language-identification-c-api spoken-language-identification-c-api.c)
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target_link_libraries(spoken-language-identification-c-api sherpa-onnx-c-api)
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if(SHERPA_ONNX_HAS_ALSA)
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add_subdirectory(./asr-microphone-example)
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else()
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elseif((UNIX AND NOT APPLE) OR LINUX)
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message(WARNING "Not include ./asr-microphone-example since alsa is not available")
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endif()
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@@ -4,7 +4,7 @@ CUR_DIR :=$(shell pwd)
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CFLAGS := -I ../ -I ../build/_deps/cargs-src/include/
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LDFLAGS := -L ../build/lib
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LDFLAGS += -L ../build/_deps/onnxruntime-src/lib
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LDFLAGS += -lsherpa-onnx-c-api -lsherpa-onnx-core -lonnxruntime -lkaldi-native-fbank-core -lkaldi-decoder-core -lsherpa-onnx-kaldifst-core -lsherpa-onnx-fst -lcargs
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LDFLAGS += -lsherpa-onnx-c-api -lsherpa-onnx-core -lkaldi-decoder-core -lsherpa-onnx-kaldifst-core -lsherpa-onnx-fst -lkaldi-native-fbank-core -lpiper_phonemize -lespeak-ng -lucd -lcargs -lonnxruntime
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LDFLAGS += -framework Foundation
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LDFLAGS += -lc++
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LDFLAGS += -Wl,-rpath,${CUR_DIR}/../build/lib
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@@ -169,55 +169,56 @@ int32_t main(int32_t argc, char *argv[]) {
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int32_t segment_id = 0;
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const char *wav_filename = argv[context.index];
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FILE *fp = fopen(wav_filename, "rb");
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if (!fp) {
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fprintf(stderr, "Failed to open %s\n", wav_filename);
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const SherpaOnnxWave *wave = SherpaOnnxReadWave(wav_filename);
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if (wave == NULL) {
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fprintf(stderr, "Failed to read %s\n", wav_filename);
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return -1;
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}
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// Assume the wave header occupies 44 bytes.
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fseek(fp, 44, SEEK_SET);
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// simulate streaming
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#define N 3200 // 0.2 s. Sample rate is fixed to 16 kHz
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int16_t buffer[N];
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float samples[N];
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fprintf(stderr, "sample rate: %d, num samples: %d, duration: %.2f s\n",
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wave->sample_rate, wave->num_samples,
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(float)wave->num_samples / wave->sample_rate);
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while (!feof(fp)) {
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size_t n = fread((void *)buffer, sizeof(int16_t), N, fp);
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if (n > 0) {
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for (size_t i = 0; i != n; ++i) {
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samples[i] = buffer[i] / 32768.;
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}
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AcceptWaveform(stream, 16000, samples, n);
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while (IsOnlineStreamReady(recognizer, stream)) {
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DecodeOnlineStream(recognizer, stream);
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}
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int32_t k = 0;
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while (k < wave->num_samples) {
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int32_t start = k;
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int32_t end =
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(start + N > wave->num_samples) ? wave->num_samples : (start + N);
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k += N;
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const SherpaOnnxOnlineRecognizerResult *r =
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GetOnlineStreamResult(recognizer, stream);
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if (strlen(r->text)) {
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SherpaOnnxPrint(display, segment_id, r->text);
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}
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if (IsEndpoint(recognizer, stream)) {
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if (strlen(r->text)) {
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++segment_id;
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}
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Reset(recognizer, stream);
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}
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DestroyOnlineRecognizerResult(r);
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AcceptWaveform(stream, wave->sample_rate, wave->samples + start,
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end - start);
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while (IsOnlineStreamReady(recognizer, stream)) {
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DecodeOnlineStream(recognizer, stream);
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}
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const SherpaOnnxOnlineRecognizerResult *r =
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GetOnlineStreamResult(recognizer, stream);
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if (strlen(r->text)) {
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SherpaOnnxPrint(display, segment_id, r->text);
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}
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if (IsEndpoint(recognizer, stream)) {
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if (strlen(r->text)) {
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++segment_id;
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}
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Reset(recognizer, stream);
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}
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DestroyOnlineRecognizerResult(r);
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}
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fclose(fp);
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// add some tail padding
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float tail_paddings[4800] = {0}; // 0.3 seconds at 16 kHz sample rate
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AcceptWaveform(stream, 16000, tail_paddings, 4800);
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AcceptWaveform(stream, wave->sample_rate, tail_paddings, 4800);
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SherpaOnnxFreeWave(wave);
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InputFinished(stream);
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while (IsOnlineStreamReady(recognizer, stream)) {
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65
c-api-examples/spoken-language-identification-c-api.c
Normal file
65
c-api-examples/spoken-language-identification-c-api.c
Normal file
@@ -0,0 +1,65 @@
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// We assume you have pre-downloaded the whisper multi-lingual models
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// from https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
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// An example command to download the "tiny" whisper model is given below:
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//
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// clang-format off
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//
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// wget 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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//
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// clang-format on
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#include <stdio.h>
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#include <stdlib.h>
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#include <string.h>
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#include "sherpa-onnx/c-api/c-api.h"
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int32_t main() {
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SherpaOnnxSpokenLanguageIdentificationConfig config;
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memset(&config, 0, sizeof(config));
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config.whisper.encoder = "./sherpa-onnx-whisper-tiny/tiny-encoder.int8.onnx";
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config.whisper.decoder = "./sherpa-onnx-whisper-tiny/tiny-decoder.int8.onnx";
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config.num_threads = 1;
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config.debug = 1;
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config.provider = "cpu";
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const SherpaOnnxSpokenLanguageIdentification *slid =
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SherpaOnnxCreateSpokenLanguageIdentification(&config);
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if (!slid) {
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fprintf(stderr, "Failed to create spoken language identifier");
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return -1;
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}
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// You can find more test waves from
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// https://hf-mirror.com/spaces/k2-fsa/spoken-language-identification/tree/main/test_wavs
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const char *wav_filename = "./sherpa-onnx-whisper-tiny/test_wavs/0.wav";
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const SherpaOnnxWave *wave = SherpaOnnxReadWave(wav_filename);
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if (wave == NULL) {
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fprintf(stderr, "Failed to read %s\n", wav_filename);
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return -1;
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}
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SherpaOnnxOfflineStream *stream =
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SherpaOnnxSpokenLanguageIdentificationCreateOfflineStream(slid);
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AcceptWaveformOffline(stream, wave->sample_rate, wave->samples,
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wave->num_samples);
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const SherpaOnnxSpokenLanguageIdentificationResult *result =
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SherpaOnnxSpokenLanguageIdentificationCompute(slid, stream);
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fprintf(stderr, "wav_filename: %s\n", wav_filename);
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fprintf(stderr, "Detected language: %s\n", result->lang);
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SherpaOnnxDestroySpokenLanguageIdentificationResult(result);
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DestroyOfflineStream(stream);
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SherpaOnnxFreeWave(wave);
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SherpaOnnxDestroySpokenLanguageIdentification(slid);
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return 0;
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}
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