Add C API for spoken language identification. (#695)

This commit is contained in:
Fangjun Kuang
2024-03-25 15:16:47 +08:00
committed by GitHub
parent 0d258dd150
commit ab7cff2513
18 changed files with 366 additions and 70 deletions

View File

@@ -7,8 +7,11 @@ target_link_libraries(decode-file-c-api sherpa-onnx-c-api cargs)
add_executable(offline-tts-c-api offline-tts-c-api.c)
target_link_libraries(offline-tts-c-api sherpa-onnx-c-api cargs)
add_executable(spoken-language-identification-c-api spoken-language-identification-c-api.c)
target_link_libraries(spoken-language-identification-c-api sherpa-onnx-c-api)
if(SHERPA_ONNX_HAS_ALSA)
add_subdirectory(./asr-microphone-example)
else()
elseif((UNIX AND NOT APPLE) OR LINUX)
message(WARNING "Not include ./asr-microphone-example since alsa is not available")
endif()

View File

@@ -4,7 +4,7 @@ CUR_DIR :=$(shell pwd)
CFLAGS := -I ../ -I ../build/_deps/cargs-src/include/
LDFLAGS := -L ../build/lib
LDFLAGS += -L ../build/_deps/onnxruntime-src/lib
LDFLAGS += -lsherpa-onnx-c-api -lsherpa-onnx-core -lonnxruntime -lkaldi-native-fbank-core -lkaldi-decoder-core -lsherpa-onnx-kaldifst-core -lsherpa-onnx-fst -lcargs
LDFLAGS += -lsherpa-onnx-c-api -lsherpa-onnx-core -lkaldi-decoder-core -lsherpa-onnx-kaldifst-core -lsherpa-onnx-fst -lkaldi-native-fbank-core -lpiper_phonemize -lespeak-ng -lucd -lcargs -lonnxruntime
LDFLAGS += -framework Foundation
LDFLAGS += -lc++
LDFLAGS += -Wl,-rpath,${CUR_DIR}/../build/lib

View File

@@ -169,55 +169,56 @@ int32_t main(int32_t argc, char *argv[]) {
int32_t segment_id = 0;
const char *wav_filename = argv[context.index];
FILE *fp = fopen(wav_filename, "rb");
if (!fp) {
fprintf(stderr, "Failed to open %s\n", wav_filename);
const SherpaOnnxWave *wave = SherpaOnnxReadWave(wav_filename);
if (wave == NULL) {
fprintf(stderr, "Failed to read %s\n", wav_filename);
return -1;
}
// Assume the wave header occupies 44 bytes.
fseek(fp, 44, SEEK_SET);
// simulate streaming
#define N 3200 // 0.2 s. Sample rate is fixed to 16 kHz
int16_t buffer[N];
float samples[N];
fprintf(stderr, "sample rate: %d, num samples: %d, duration: %.2f s\n",
wave->sample_rate, wave->num_samples,
(float)wave->num_samples / wave->sample_rate);
while (!feof(fp)) {
size_t n = fread((void *)buffer, sizeof(int16_t), N, fp);
if (n > 0) {
for (size_t i = 0; i != n; ++i) {
samples[i] = buffer[i] / 32768.;
}
AcceptWaveform(stream, 16000, samples, n);
while (IsOnlineStreamReady(recognizer, stream)) {
DecodeOnlineStream(recognizer, stream);
}
int32_t k = 0;
while (k < wave->num_samples) {
int32_t start = k;
int32_t end =
(start + N > wave->num_samples) ? wave->num_samples : (start + N);
k += N;
const SherpaOnnxOnlineRecognizerResult *r =
GetOnlineStreamResult(recognizer, stream);
if (strlen(r->text)) {
SherpaOnnxPrint(display, segment_id, r->text);
}
if (IsEndpoint(recognizer, stream)) {
if (strlen(r->text)) {
++segment_id;
}
Reset(recognizer, stream);
}
DestroyOnlineRecognizerResult(r);
AcceptWaveform(stream, wave->sample_rate, wave->samples + start,
end - start);
while (IsOnlineStreamReady(recognizer, stream)) {
DecodeOnlineStream(recognizer, stream);
}
const SherpaOnnxOnlineRecognizerResult *r =
GetOnlineStreamResult(recognizer, stream);
if (strlen(r->text)) {
SherpaOnnxPrint(display, segment_id, r->text);
}
if (IsEndpoint(recognizer, stream)) {
if (strlen(r->text)) {
++segment_id;
}
Reset(recognizer, stream);
}
DestroyOnlineRecognizerResult(r);
}
fclose(fp);
// add some tail padding
float tail_paddings[4800] = {0}; // 0.3 seconds at 16 kHz sample rate
AcceptWaveform(stream, 16000, tail_paddings, 4800);
AcceptWaveform(stream, wave->sample_rate, tail_paddings, 4800);
SherpaOnnxFreeWave(wave);
InputFinished(stream);
while (IsOnlineStreamReady(recognizer, stream)) {

View File

@@ -0,0 +1,65 @@
// We assume you have pre-downloaded the whisper multi-lingual models
// from https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
// An example command to download the "tiny" whisper model is given below:
//
// clang-format off
//
// wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-whisper-tiny.tar.bz2
// tar xvf sherpa-onnx-whisper-tiny.tar.bz2
// rm sherpa-onnx-whisper-tiny.tar.bz2
//
// clang-format on
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include "sherpa-onnx/c-api/c-api.h"
int32_t main() {
SherpaOnnxSpokenLanguageIdentificationConfig config;
memset(&config, 0, sizeof(config));
config.whisper.encoder = "./sherpa-onnx-whisper-tiny/tiny-encoder.int8.onnx";
config.whisper.decoder = "./sherpa-onnx-whisper-tiny/tiny-decoder.int8.onnx";
config.num_threads = 1;
config.debug = 1;
config.provider = "cpu";
const SherpaOnnxSpokenLanguageIdentification *slid =
SherpaOnnxCreateSpokenLanguageIdentification(&config);
if (!slid) {
fprintf(stderr, "Failed to create spoken language identifier");
return -1;
}
// You can find more test waves from
// https://hf-mirror.com/spaces/k2-fsa/spoken-language-identification/tree/main/test_wavs
const char *wav_filename = "./sherpa-onnx-whisper-tiny/test_wavs/0.wav";
const SherpaOnnxWave *wave = SherpaOnnxReadWave(wav_filename);
if (wave == NULL) {
fprintf(stderr, "Failed to read %s\n", wav_filename);
return -1;
}
SherpaOnnxOfflineStream *stream =
SherpaOnnxSpokenLanguageIdentificationCreateOfflineStream(slid);
AcceptWaveformOffline(stream, wave->sample_rate, wave->samples,
wave->num_samples);
const SherpaOnnxSpokenLanguageIdentificationResult *result =
SherpaOnnxSpokenLanguageIdentificationCompute(slid, stream);
fprintf(stderr, "wav_filename: %s\n", wav_filename);
fprintf(stderr, "Detected language: %s\n", result->lang);
SherpaOnnxDestroySpokenLanguageIdentificationResult(result);
DestroyOfflineStream(stream);
SherpaOnnxFreeWave(wave);
SherpaOnnxDestroySpokenLanguageIdentification(slid);
return 0;
}