lxiao336
Committed by GitHub

Allow more online models to load tokens file from the memory (#1352)

Co-authored-by: xiao <shawl336@6163.com>
... ... @@ -120,3 +120,99 @@ jobs:
./streaming-zipformer-buffered-tokens-hotwords-c-api
rm -rf sherpa-onnx-streaming-zipformer-*
- name: Test streaming paraformer with tokens loaded from buffers
shell: bash
run: |
gcc -o streaming-paraformer-buffered-tokens-c-api ./c-api-examples/streaming-paraformer-buffered-tokens-c-api.c \
-I ./build/install/include \
-L ./build/install/lib/ \
-l sherpa-onnx-c-api \
-l onnxruntime
ls -lh streaming-paraformer-buffered-tokens-c-api
if [[ ${{ matrix.os }} == ubuntu-latest ]]; then
ldd ./streaming-paraformer-buffered-tokens-c-api
echo "----"
readelf -d ./streaming-paraformer-buffered-tokens-c-api
fi
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-paraformer-bilingual-zh-en.tar.bz2
tar xvf sherpa-onnx-streaming-paraformer-bilingual-zh-en.tar.bz2
rm sherpa-onnx-streaming-paraformer-bilingual-zh-en.tar.bz2
ls -lh sherpa-onnx-streaming-paraformer-bilingual-zh-en
echo "---"
ls -lh sherpa-onnx-streaming-paraformer-bilingual-zh-en/test_wavs
export LD_LIBRARY_PATH=$PWD/build/install/lib:$LD_LIBRARY_PATH
export DYLD_LIBRARY_PATH=$PWD/build/install/lib:$DYLD_LIBRARY_PATH
./streaming-paraformer-buffered-tokens-c-api
rm -rf sherpa-onnx-streaming-paraformer-*
- name: Test streaming ctc with tokens loaded from buffers
shell: bash
run: |
gcc -o streaming-ctc-buffered-tokens-c-api ./c-api-examples/streaming-ctc-buffered-tokens-c-api.c \
-I ./build/install/include \
-L ./build/install/lib/ \
-l sherpa-onnx-c-api \
-l onnxruntime
ls -lh streaming-ctc-buffered-tokens-c-api
if [[ ${{ matrix.os }} == ubuntu-latest ]]; then
ldd ./streaming-ctc-buffered-tokens-c-api
echo "----"
readelf -d ./streaming-ctc-buffered-tokens-c-api
fi
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13.tar.bz2
tar xvf sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13.tar.bz2
rm sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13.tar.bz2
ls -lh sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13
echo "---"
ls -lh sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13/test_wavs
export LD_LIBRARY_PATH=$PWD/build/install/lib:$LD_LIBRARY_PATH
export DYLD_LIBRARY_PATH=$PWD/build/install/lib:$DYLD_LIBRARY_PATH
./streaming-ctc-buffered-tokens-c-api
rm -rf sherpa-onnx-streaming-ctc-*
- name: Test keywords spotting with tokens and keywords loaded from buffers
shell: bash
run: |
gcc -o keywords-spotter-buffered-tokens-keywords-c-api ./c-api-examples/keywords-spotter-buffered-tokens-keywords-c-api.c \
-I ./build/install/include \
-L ./build/install/lib/ \
-l sherpa-onnx-c-api \
-l onnxruntime
ls -lh keywords-spotter-buffered-tokens-keywords-c-api
if [[ ${{ matrix.os }} == ubuntu-latest ]]; then
ldd ./keywords-spotter-buffered-tokens-keywords-c-api
echo "----"
readelf -d ./keywords-spotter-buffered-tokens-keywords-c-api
fi
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/kws-models/sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01-mobile.tar.bz2
tar xvf sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01-mobile.tar.bz2
rm sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01-mobile.tar.bz2
ls -lh sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01-mobile
echo "---"
ls -lh sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01-mobile/test_wavs
export LD_LIBRARY_PATH=$PWD/build/install/lib:$LD_LIBRARY_PATH
export DYLD_LIBRARY_PATH=$PWD/build/install/lib:$DYLD_LIBRARY_PATH
./keywords-spotter-buffered-tokens-keywords-c-api
rm -rf sherpa-onnx-kws-zipformer-*
\ No newline at end of file
... ...
... ... @@ -52,6 +52,18 @@ add_executable(streaming-zipformer-buffered-tokens-hotwords-c-api
streaming-zipformer-buffered-tokens-hotwords-c-api.c)
target_link_libraries(streaming-zipformer-buffered-tokens-hotwords-c-api sherpa-onnx-c-api)
add_executable(streaming-paraformer-buffered-tokens-c-api
streaming-paraformer-buffered-tokens-c-api.c)
target_link_libraries(streaming-paraformer-buffered-tokens-c-api sherpa-onnx-c-api)
add_executable(streaming-ctc-buffered-tokens-c-api
streaming-ctc-buffered-tokens-c-api.c)
target_link_libraries(streaming-ctc-buffered-tokens-c-api sherpa-onnx-c-api)
add_executable(keywords-spotter-buffered-tokens-keywords-c-api
keywords-spotter-buffered-tokens-keywords-c-api.c)
target_link_libraries(keywords-spotter-buffered-tokens-keywords-c-api sherpa-onnx-c-api)
if(SHERPA_ONNX_HAS_ALSA)
add_subdirectory(./asr-microphone-example)
elseif((UNIX AND NOT APPLE) OR LINUX)
... ...
// c-api-examples/keywords-spotter-buffered-tokens-keywords-c-api.c
//
// Copyright (c) 2024 Xiaomi Corporation
// Copyright (c) 2024 Luo Xiao
//
// This file demonstrates how to use keywords spotter with sherpa-onnx's C
// API and with tokens and keywords loaded from buffered strings instead of from
// external files API.
// clang-format off
//
// wget https://github.com/k2-fsa/sherpa-onnx/releases/download/kws-models/sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01-mobile.tar.bz2
// tar xvf sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01-mobile.tar.bz2
// rm sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01-mobile.tar.bz2
//
// clang-format on
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include "sherpa-onnx/c-api/c-api.h"
static size_t ReadFile(const char *filename, const char **buffer_out) {
FILE *file = fopen(filename, "r");
if (file == NULL) {
fprintf(stderr, "Failed to open %s\n", filename);
return -1;
}
fseek(file, 0L, SEEK_END);
long size = ftell(file);
rewind(file);
*buffer_out = malloc(size);
if (*buffer_out == NULL) {
fclose(file);
fprintf(stderr, "Memory error\n");
return -1;
}
size_t read_bytes = fread(*buffer_out, 1, size, file);
if (read_bytes != size) {
printf("Errors occured in reading the file %s\n", filename);
free((void *)*buffer_out);
*buffer_out = NULL;
fclose(file);
return -1;
}
fclose(file);
return read_bytes;
}
int32_t main() {
const char *wav_filename =
"sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01-mobile/test_wavs/"
"6.wav";
const char *encoder_filename =
"sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01-mobile/"
"encoder-epoch-12-avg-2-chunk-16-left-64.int8.onnx";
const char *decoder_filename =
"sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01-mobile/"
"decoder-epoch-12-avg-2-chunk-16-left-64.onnx";
const char *joiner_filename =
"sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01-mobile/"
"joiner-epoch-12-avg-2-chunk-16-left-64.int8.onnx";
const char *provider = "cpu";
const char *tokens_filename =
"sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01-mobile/tokens.txt";
const char *keywords_filename =
"sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01-mobile/test_wavs/"
"test_keywords.txt";
const SherpaOnnxWave *wave = SherpaOnnxReadWave(wav_filename);
if (wave == NULL) {
fprintf(stderr, "Failed to read %s\n", wav_filename);
return -1;
}
// reading tokens and keywords to buffers
const char *tokens_buf;
size_t token_buf_size = ReadFile(tokens_filename, &tokens_buf);
if (token_buf_size < 1) {
fprintf(stderr, "Please check your tokens.txt!\n");
free((void *)tokens_buf);
return -1;
}
const char *keywords_buf;
size_t keywords_buf_size = ReadFile(keywords_filename, &keywords_buf);
if (keywords_buf_size < 1) {
fprintf(stderr, "Please check your keywords.txt!\n");
free((void *)keywords_buf);
return -1;
}
// Zipformer config
SherpaOnnxOnlineTransducerModelConfig zipformer_config;
memset(&zipformer_config, 0, sizeof(zipformer_config));
zipformer_config.encoder = encoder_filename;
zipformer_config.decoder = decoder_filename;
zipformer_config.joiner = joiner_filename;
// Online model config
SherpaOnnxOnlineModelConfig online_model_config;
memset(&online_model_config, 0, sizeof(online_model_config));
online_model_config.debug = 1;
online_model_config.num_threads = 1;
online_model_config.provider = provider;
online_model_config.tokens_buf = tokens_buf;
online_model_config.tokens_buf_size = token_buf_size;
online_model_config.transducer = zipformer_config;
// Keywords-spotter config
SherpaOnnxKeywordSpotterConfig keywords_spotter_config;
memset(&keywords_spotter_config, 0, sizeof(keywords_spotter_config));
keywords_spotter_config.max_active_paths = 4;
keywords_spotter_config.keywords_threshold = 0.1;
keywords_spotter_config.keywords_score = 3.0;
keywords_spotter_config.model_config = online_model_config;
keywords_spotter_config.keywords_buf = keywords_buf;
keywords_spotter_config.keywords_buf_size = keywords_buf_size;
SherpaOnnxKeywordSpotter *keywords_spotter =
SherpaOnnxCreateKeywordSpotter(&keywords_spotter_config);
free((void *)tokens_buf);
tokens_buf = NULL;
free((void *)keywords_buf);
keywords_buf = NULL;
if (keywords_spotter == NULL) {
fprintf(stderr, "Please check your config!\n");
SherpaOnnxFreeWave(wave);
return -1;
}
SherpaOnnxOnlineStream *stream =
SherpaOnnxCreateKeywordStream(keywords_spotter);
const SherpaOnnxDisplay *display = SherpaOnnxCreateDisplay(50);
int32_t segment_id = 0;
// simulate streaming. You can choose an arbitrary N
#define N 3200
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);
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;
SherpaOnnxOnlineStreamAcceptWaveform(stream, wave->sample_rate,
wave->samples + start, end - start);
while (SherpaOnnxIsKeywordStreamReady(keywords_spotter, stream)) {
SherpaOnnxDecodeKeywordStream(keywords_spotter, stream);
}
const SherpaOnnxKeywordResult *r =
SherpaOnnxGetKeywordResult(keywords_spotter, stream);
if (strlen(r->keyword)) {
SherpaOnnxPrint(display, segment_id, r->keyword);
}
SherpaOnnxDestroyKeywordResult(r);
}
// add some tail padding
float tail_paddings[4800] = {0}; // 0.3 seconds at 16 kHz sample rate
SherpaOnnxOnlineStreamAcceptWaveform(stream, wave->sample_rate, tail_paddings,
4800);
SherpaOnnxFreeWave(wave);
SherpaOnnxOnlineStreamInputFinished(stream);
while (SherpaOnnxIsKeywordStreamReady(keywords_spotter, stream)) {
SherpaOnnxDecodeKeywordStream(keywords_spotter, stream);
}
const SherpaOnnxKeywordResult *r =
SherpaOnnxGetKeywordResult(keywords_spotter, stream);
if (strlen(r->keyword)) {
SherpaOnnxPrint(display, segment_id, r->keyword);
}
SherpaOnnxDestroyKeywordResult(r);
SherpaOnnxDestroyDisplay(display);
SherpaOnnxDestroyOnlineStream(stream);
SherpaOnnxDestroyKeywordSpotter(keywords_spotter);
fprintf(stderr, "\n");
return 0;
}
... ...
// c-api-examples/streaming-ctc-buffered-tokens-c-api.c
//
// Copyright (c) 2024 Xiaomi Corporation
// Copyright (c) 2024 Luo Xiao
//
// This file demonstrates how to use streaming Zipformer2 Ctc with sherpa-onnx's
// C API and with tokens loaded from buffered strings instead of
// from external files API.
// clang-format off
//
// wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13.tar.bz2
// tar xvf sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13.tar.bz2
// rm sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13.tar.bz2
//
// clang-format on
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include "sherpa-onnx/c-api/c-api.h"
static size_t ReadFile(const char *filename, const char **buffer_out) {
FILE *file = fopen(filename, "r");
if (file == NULL) {
fprintf(stderr, "Failed to open %s\n", filename);
return -1;
}
fseek(file, 0L, SEEK_END);
long size = ftell(file);
rewind(file);
*buffer_out = malloc(size);
if (*buffer_out == NULL) {
fclose(file);
fprintf(stderr, "Memory error\n");
return -1;
}
size_t read_bytes = fread(*buffer_out, 1, size, file);
if (read_bytes != size) {
printf("Errors occured in reading the file %s\n", filename);
free((void *)*buffer_out);
*buffer_out = NULL;
fclose(file);
return -1;
}
fclose(file);
return read_bytes;
}
int32_t main() {
const char *wav_filename =
"sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13/test_wavs/"
"DEV_T0000000000.wav";
const char *model_filename =
"sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13/"
"ctc-epoch-20-avg-1-chunk-16-left-128.int8.onnx";
const char *tokens_filename =
"sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13/tokens.txt";
const char *provider = "cpu";
const SherpaOnnxWave *wave = SherpaOnnxReadWave(wav_filename);
if (wave == NULL) {
fprintf(stderr, "Failed to read %s\n", wav_filename);
return -1;
}
// reading tokens to buffers
const char *tokens_buf;
size_t token_buf_size = ReadFile(tokens_filename, &tokens_buf);
if (token_buf_size < 1) {
fprintf(stderr, "Please check your tokens.txt!\n");
free((void *)tokens_buf);
return -1;
}
// Zipformer2Ctc config
SherpaOnnxOnlineZipformer2CtcModelConfig zipformer2_ctc_config;
memset(&zipformer2_ctc_config, 0, sizeof(zipformer2_ctc_config));
zipformer2_ctc_config.model = model_filename;
// Online model config
SherpaOnnxOnlineModelConfig online_model_config;
memset(&online_model_config, 0, sizeof(online_model_config));
online_model_config.debug = 1;
online_model_config.num_threads = 1;
online_model_config.provider = provider;
online_model_config.tokens_buf = tokens_buf;
online_model_config.tokens_buf_size = token_buf_size;
online_model_config.zipformer2_ctc = zipformer2_ctc_config;
// Recognizer config
SherpaOnnxOnlineRecognizerConfig recognizer_config;
memset(&recognizer_config, 0, sizeof(recognizer_config));
recognizer_config.decoding_method = "greedy_search";
recognizer_config.model_config = online_model_config;
SherpaOnnxOnlineRecognizer *recognizer =
SherpaOnnxCreateOnlineRecognizer(&recognizer_config);
free((void *)tokens_buf);
tokens_buf = NULL;
if (recognizer == NULL) {
fprintf(stderr, "Please check your config!\n");
SherpaOnnxFreeWave(wave);
return -1;
}
SherpaOnnxOnlineStream *stream = SherpaOnnxCreateOnlineStream(recognizer);
const SherpaOnnxDisplay *display = SherpaOnnxCreateDisplay(50);
int32_t segment_id = 0;
// simulate streaming. You can choose an arbitrary N
#define N 3200
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);
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;
SherpaOnnxOnlineStreamAcceptWaveform(stream, wave->sample_rate,
wave->samples + start, end - start);
while (SherpaOnnxIsOnlineStreamReady(recognizer, stream)) {
SherpaOnnxDecodeOnlineStream(recognizer, stream);
}
const SherpaOnnxOnlineRecognizerResult *r =
SherpaOnnxGetOnlineStreamResult(recognizer, stream);
if (strlen(r->text)) {
SherpaOnnxPrint(display, segment_id, r->text);
}
if (SherpaOnnxOnlineStreamIsEndpoint(recognizer, stream)) {
if (strlen(r->text)) {
++segment_id;
}
SherpaOnnxOnlineStreamReset(recognizer, stream);
}
SherpaOnnxDestroyOnlineRecognizerResult(r);
}
// add some tail padding
float tail_paddings[4800] = {0}; // 0.3 seconds at 16 kHz sample rate
SherpaOnnxOnlineStreamAcceptWaveform(stream, wave->sample_rate, tail_paddings,
4800);
SherpaOnnxFreeWave(wave);
SherpaOnnxOnlineStreamInputFinished(stream);
while (SherpaOnnxIsOnlineStreamReady(recognizer, stream)) {
SherpaOnnxDecodeOnlineStream(recognizer, stream);
}
const SherpaOnnxOnlineRecognizerResult *r =
SherpaOnnxGetOnlineStreamResult(recognizer, stream);
if (strlen(r->text)) {
SherpaOnnxPrint(display, segment_id, r->text);
}
SherpaOnnxDestroyOnlineRecognizerResult(r);
SherpaOnnxDestroyDisplay(display);
SherpaOnnxDestroyOnlineStream(stream);
SherpaOnnxDestroyOnlineRecognizer(recognizer);
fprintf(stderr, "\n");
return 0;
}
... ...
// c-api-examples/streaming-paraformer-buffered-tokens-c-api.c
//
// Copyright (c) 2024 Xiaomi Corporation
// Copyright (c) 2024 Luo Xiao
//
// This file demonstrates how to use streaming Paraformer with sherpa-onnx's C
// API and with tokens loaded from buffered strings instead of from
// external files API.
// clang-format off
//
// wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-streaming-paraformer-bilingual-zh-en.tar.bz2
// tar xvf sherpa-onnx-streaming-paraformer-bilingual-zh-en.tar.bz2
// rm sherpa-onnx-streaming-paraformer-bilingual-zh-en.tar.bz2
//
// clang-format on
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include "sherpa-onnx/c-api/c-api.h"
static size_t ReadFile(const char *filename, const char **buffer_out) {
FILE *file = fopen(filename, "r");
if (file == NULL) {
fprintf(stderr, "Failed to open %s\n", filename);
return -1;
}
fseek(file, 0L, SEEK_END);
long size = ftell(file);
rewind(file);
*buffer_out = malloc(size);
if (*buffer_out == NULL) {
fclose(file);
fprintf(stderr, "Memory error\n");
return -1;
}
size_t read_bytes = fread(*buffer_out, 1, size, file);
if (read_bytes != size) {
printf("Errors occured in reading the file %s\n", filename);
free((void *)*buffer_out);
*buffer_out = NULL;
fclose(file);
return -1;
}
fclose(file);
return read_bytes;
}
int32_t main() {
const char *wav_filename =
"sherpa-onnx-streaming-paraformer-bilingual-zh-en/test_wavs/0.wav";
const char *encoder_filename =
"sherpa-onnx-streaming-paraformer-bilingual-zh-en/encoder.int8.onnx";
const char *decoder_filename =
"sherpa-onnx-streaming-paraformer-bilingual-zh-en/decoder.int8.onnx";
const char *tokens_filename =
"sherpa-onnx-streaming-paraformer-bilingual-zh-en/tokens.txt";
const char *provider = "cpu";
const SherpaOnnxWave *wave = SherpaOnnxReadWave(wav_filename);
if (wave == NULL) {
fprintf(stderr, "Failed to read %s\n", wav_filename);
return -1;
}
// reading tokens to buffers
const char *tokens_buf;
size_t token_buf_size = ReadFile(tokens_filename, &tokens_buf);
if (token_buf_size < 1) {
fprintf(stderr, "Please check your tokens.txt!\n");
free((void *)tokens_buf);
return -1;
}
// Paraformer config
SherpaOnnxOnlineParaformerModelConfig paraformer_config;
memset(&paraformer_config, 0, sizeof(paraformer_config));
paraformer_config.encoder = encoder_filename;
paraformer_config.decoder = decoder_filename;
// Online model config
SherpaOnnxOnlineModelConfig online_model_config;
memset(&online_model_config, 0, sizeof(online_model_config));
online_model_config.debug = 1;
online_model_config.num_threads = 1;
online_model_config.provider = provider;
online_model_config.tokens_buf = tokens_buf;
online_model_config.tokens_buf_size = token_buf_size;
online_model_config.paraformer = paraformer_config;
// Recognizer config
SherpaOnnxOnlineRecognizerConfig recognizer_config;
memset(&recognizer_config, 0, sizeof(recognizer_config));
recognizer_config.decoding_method = "greedy_search";
recognizer_config.model_config = online_model_config;
SherpaOnnxOnlineRecognizer *recognizer =
SherpaOnnxCreateOnlineRecognizer(&recognizer_config);
free((void *)tokens_buf);
tokens_buf = NULL;
if (recognizer == NULL) {
fprintf(stderr, "Please check your config!\n");
SherpaOnnxFreeWave(wave);
return -1;
}
SherpaOnnxOnlineStream *stream = SherpaOnnxCreateOnlineStream(recognizer);
const SherpaOnnxDisplay *display = SherpaOnnxCreateDisplay(50);
int32_t segment_id = 0;
// simulate streaming. You can choose an arbitrary N
#define N 3200
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);
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;
SherpaOnnxOnlineStreamAcceptWaveform(stream, wave->sample_rate,
wave->samples + start, end - start);
while (SherpaOnnxIsOnlineStreamReady(recognizer, stream)) {
SherpaOnnxDecodeOnlineStream(recognizer, stream);
}
const SherpaOnnxOnlineRecognizerResult *r =
SherpaOnnxGetOnlineStreamResult(recognizer, stream);
if (strlen(r->text)) {
SherpaOnnxPrint(display, segment_id, r->text);
}
if (SherpaOnnxOnlineStreamIsEndpoint(recognizer, stream)) {
if (strlen(r->text)) {
++segment_id;
}
SherpaOnnxOnlineStreamReset(recognizer, stream);
}
SherpaOnnxDestroyOnlineRecognizerResult(r);
}
// add some tail padding
float tail_paddings[4800] = {0}; // 0.3 seconds at 16 kHz sample rate
SherpaOnnxOnlineStreamAcceptWaveform(stream, wave->sample_rate, tail_paddings,
4800);
SherpaOnnxFreeWave(wave);
SherpaOnnxOnlineStreamInputFinished(stream);
while (SherpaOnnxIsOnlineStreamReady(recognizer, stream)) {
SherpaOnnxDecodeOnlineStream(recognizer, stream);
}
const SherpaOnnxOnlineRecognizerResult *r =
SherpaOnnxGetOnlineStreamResult(recognizer, stream);
if (strlen(r->text)) {
SherpaOnnxPrint(display, segment_id, r->text);
}
SherpaOnnxDestroyOnlineRecognizerResult(r);
SherpaOnnxDestroyDisplay(display);
SherpaOnnxDestroyOnlineStream(stream);
SherpaOnnxDestroyOnlineRecognizer(recognizer);
fprintf(stderr, "\n");
return 0;
}
... ...
... ... @@ -5,7 +5,7 @@
//
// This file demonstrates how to use streaming Zipformer with sherpa-onnx's C
// and with tokens and hotwords loaded from buffered strings instead of from
// API and with tokens and hotwords loaded from buffered strings instead of from
// external files API.
// clang-format off
//
... ...
... ... @@ -667,6 +667,12 @@ SherpaOnnxKeywordSpotter *SherpaOnnxCreateKeywordSpotter(
spotter_config.model_config.tokens =
SHERPA_ONNX_OR(config->model_config.tokens, "");
if (config->model_config.tokens_buf &&
config->model_config.tokens_buf_size > 0) {
spotter_config.model_config.tokens_buf = std::string(
config->model_config.tokens_buf, config->model_config.tokens_buf_size);
}
spotter_config.model_config.num_threads =
SHERPA_ONNX_OR(config->model_config.num_threads, 1);
spotter_config.model_config.provider_config.provider =
... ... @@ -691,6 +697,10 @@ SherpaOnnxKeywordSpotter *SherpaOnnxCreateKeywordSpotter(
SHERPA_ONNX_OR(config->keywords_threshold, 0.25);
spotter_config.keywords_file = SHERPA_ONNX_OR(config->keywords_file, "");
if (config->keywords_buf && config->keywords_buf_size > 0) {
spotter_config.keywords_buf =
std::string(config->keywords_buf, config->keywords_buf_size);
}
if (config->model_config.debug) {
SHERPA_ONNX_LOGE("%s\n", spotter_config.ToString().c_str());
... ...
... ... @@ -88,8 +88,8 @@ SHERPA_ONNX_API typedef struct SherpaOnnxOnlineModelConfig {
// - cjkchar+bpe
const char *modeling_unit;
const char *bpe_vocab;
/// if non-null, loading the tokens from the buffered string directly in
/// prioriy
/// if non-null, loading the tokens from the buffer instead of from the
/// "tokens" file
const char *tokens_buf;
/// byte size excluding the trailing '\0'
int32_t tokens_buf_size;
... ... @@ -637,6 +637,11 @@ SHERPA_ONNX_API typedef struct SherpaOnnxKeywordSpotterConfig {
float keywords_score;
float keywords_threshold;
const char *keywords_file;
/// if non-null, loading the keywords from the buffer instead of from the
/// keywords_file
const char *keywords_buf;
/// byte size excluding the trailing '\0'
int32_t keywords_buf_size;
} SherpaOnnxKeywordSpotterConfig;
SHERPA_ONNX_API typedef struct SherpaOnnxKeywordSpotter
... ...
... ... @@ -66,15 +66,25 @@ class KeywordSpotterTransducerImpl : public KeywordSpotterImpl {
public:
explicit KeywordSpotterTransducerImpl(const KeywordSpotterConfig &config)
: config_(config),
model_(OnlineTransducerModel::Create(config.model_config)),
sym_(config.model_config.tokens) {
model_(OnlineTransducerModel::Create(config.model_config)) {
if (!config.model_config.tokens_buf.empty()) {
sym_ = SymbolTable(config.model_config.tokens_buf, false);
} else {
/// assuming tokens_buf and tokens are guaranteed not being both empty
sym_ = SymbolTable(config.model_config.tokens, true);
}
if (sym_.Contains("<unk>")) {
unk_id_ = sym_["<unk>"];
}
model_->SetFeatureDim(config.feat_config.feature_dim);
InitKeywords();
if (config.keywords_buf.empty()) {
InitKeywords();
} else {
InitKeywordsFromBufStr();
}
decoder_ = std::make_unique<TransducerKeywordDecoder>(
model_.get(), config_.max_active_paths, config_.num_trailing_blanks,
... ... @@ -305,6 +315,12 @@ class KeywordSpotterTransducerImpl : public KeywordSpotterImpl {
}
#endif
void InitKeywordsFromBufStr() {
// keywords_buf's content is supposed to be same as the keywords_file's
std::istringstream is(config_.keywords_buf);
InitKeywords(is);
}
void InitOnlineStream(OnlineStream *stream) const {
auto r = decoder_->GetEmptyResult();
SHERPA_ONNX_CHECK_EQ(r.hyps.Size(), 1);
... ...
... ... @@ -89,8 +89,17 @@ void KeywordSpotterConfig::Register(ParseOptions *po) {
}
bool KeywordSpotterConfig::Validate() const {
if (keywords_file.empty()) {
SHERPA_ONNX_LOGE("Please provide --keywords-file.");
if (!keywords_file.empty() && !keywords_buf.empty()) {
SHERPA_ONNX_LOGE(
"you can not provide a keywords_buf and a keywords file: '%s', "
"at the same time, which is confusing",
keywords_file.c_str());
return false;
}
if (keywords_file.empty() && keywords_buf.empty()) {
SHERPA_ONNX_LOGE(
"Please provide either a keywords-file or the keywords-buf");
return false;
}
... ... @@ -99,7 +108,7 @@ bool KeywordSpotterConfig::Validate() const {
// keywords file will be packaged into the sherpa-onnx-wasm-kws-main.data file
// Solution: take keyword_file variable is directly
// parsed as a string of keywords
if (!std::ifstream(keywords_file.c_str()).good()) {
if (keywords_buf.empty() && !std::ifstream(keywords_file.c_str()).good()) {
SHERPA_ONNX_LOGE("Keywords file '%s' does not exist.",
keywords_file.c_str());
return false;
... ...
... ... @@ -69,6 +69,11 @@ struct KeywordSpotterConfig {
std::string keywords_file;
/// if keywords_buf is non-empty,
/// the keywords will be loaded from the buffer instead of from the
/// "keywrods_file"
std::string keywords_buf;
KeywordSpotterConfig() = default;
KeywordSpotterConfig(const FeatureExtractorConfig &feat_config,
... ...
... ... @@ -46,8 +46,8 @@ struct OnlineModelConfig {
std::string bpe_vocab;
/// if tokens_buf is non-empty,
/// the tokens will be loaded from the buffered string instead of from the
/// ${tokens} file
/// the tokens will be loaded from the buffer instead of from the
/// "tokens" file
std::string tokens_buf;
OnlineModelConfig() = default;
... ...
... ... @@ -71,8 +71,14 @@ class OnlineRecognizerCtcImpl : public OnlineRecognizerImpl {
: OnlineRecognizerImpl(config),
config_(config),
model_(OnlineCtcModel::Create(config.model_config)),
sym_(config.model_config.tokens),
endpoint_(config_.endpoint_config) {
if (!config.model_config.tokens_buf.empty()) {
sym_ = SymbolTable(config.model_config.tokens_buf, false);
} else {
/// assuming tokens_buf and tokens are guaranteed not being both empty
sym_ = SymbolTable(config.model_config.tokens, true);
}
if (!config.model_config.wenet_ctc.model.empty()) {
// WeNet CTC models assume input samples are in the range
// [-32768, 32767], so we set normalize_samples to false
... ...
... ... @@ -99,8 +99,14 @@ class OnlineRecognizerParaformerImpl : public OnlineRecognizerImpl {
: OnlineRecognizerImpl(config),
config_(config),
model_(config.model_config),
sym_(config.model_config.tokens),
endpoint_(config_.endpoint_config) {
if (!config.model_config.tokens_buf.empty()) {
sym_ = SymbolTable(config.model_config.tokens_buf, false);
} else {
/// assuming tokens_buf and tokens are guaranteed not being both empty
sym_ = SymbolTable(config.model_config.tokens, true);
}
if (config.decoding_method != "greedy_search") {
SHERPA_ONNX_LOGE(
"Unsupported decoding method: %s. Support only greedy_search at "
... ...
... ... @@ -107,8 +107,8 @@ struct OnlineRecognizerConfig {
std::string rule_fars;
/// used only for modified_beam_search, if hotwords_buf is non-empty,
/// the hotwords will be loaded from the buffered string instead of from
/// ${hotwords_file}
/// the hotwords will be loaded from the buffered string instead of from the
/// "hotwords_file"
std::string hotwords_buf;
OnlineRecognizerConfig() = default;
... ...