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examples : add VAD speech segments example (#3147)

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This commit adds an example that demonstrates how to use a VAD (Voice
Activity Detection) model to segment an audio file into speech segments.

Resolves: https://github.com/ggml-org/whisper.cpp/issues/3144
This commit is contained in:
Daniel Bevenius 2025-05-13 12:31:00 +02:00 committed by GitHub
parent b2513a6208
commit fbad8058c4
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1
examples/CMakeLists.txt
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@ -105,6 +105,7 @@ else()
add_subdirectory(bench)
add_subdirectory(server)
add_subdirectory(quantize)
add_subdirectory(vad-speech-segments)
if (WHISPER_SDL2)
add_subdirectory(stream)
add_subdirectory(command)

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examples/vad-speech-segments/CMakeLists.txt Normal file
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set(TARGET vad-speech-segments)
add_executable(${TARGET} speech.cpp)
include(DefaultTargetOptions)
target_link_libraries(${TARGET} PRIVATE common whisper ${FFMPEG_LIBRARIES} ${CMAKE_THREAD_LIBS_INIT})
install(TARGETS ${TARGET} RUNTIME)

52
examples/vad-speech-segments/README.md Normal file
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# whisper.cpp/examples/vad-speech-segments
This examples demonstrates how to use a VAD (Voice Activity Detection) model to
segment an audio file into speech segments.
### Building the example
The example can be built using the following command:
```console
cmake -S . -B build
cmake --build build -j8 --target vad-speech-segments
```
### Running the example
The examples can be run using the following command, which uses a model
that we use internally for testing:
```console
./build/bin/vad-speech-segments \
-vad-model models/for-tests-silero-v5.1.2-ggml.bin \
--file samples/jfk.wav \
--no-prints
Detected 5 speech segments:
Speech segment 0: start = 0.29, end = 2.21
Speech segment 1: start = 3.30, end = 3.77
Speech segment 2: start = 4.00, end = 4.35
Speech segment 3: start = 5.38, end = 7.65
Speech segment 4: start = 8.16, end = 10.59
```
To see more output from whisper.cpp remove the `--no-prints` argument.
### Command line options
```console
./build/bin/vad-speech-segments --help
usage: ./build/bin/vad-speech-segments [options] file
supported audio formats: flac, mp3, ogg, wav
options:
-h, --help [default] show this help message and exit
-f FNAME, --file FNAME [ ] input audio file path
-t N, --threads N [4 ] number of threads to use during computation
-ug, --use-gpu [true ] use GPU
-vm FNAME, --vad-model FNAME [ ] VAD model path
-vt N, --vad-threshold N [0.50 ] VAD threshold for speech recognition
-vspd N, --vad-min-speech-duration-ms N [250 ] VAD min speech duration (0.0-1.0)
-vsd N, --vad-min-silence-duration-ms N [100 ] VAD min silence duration (to split segments)
-vmsd N, --vad-max-speech-duration-s N [FLT_MAX] VAD max speech duration (auto-split longer)
-vp N, --vad-speech-pad-ms N [30 ] VAD speech padding (extend segments)
-vo N, --vad-samples-overlap N [0.10 ] VAD samples overlap (seconds between segments)
-np, --no-prints [false ] do not print anything other than the results
```

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examples/vad-speech-segments/speech.cpp Normal file
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#include "common.h"
#include "common-whisper.h"
#include "whisper.h"
#include <cstdio>
#include <cfloat>
#include <string>
// command-line parameters
struct cli_params {
int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
std::string vad_model = "";
float vad_threshold = 0.5f;
int vad_min_speech_duration_ms = 250;
int vad_min_silence_duration_ms = 100;
float vad_max_speech_duration_s = FLT_MAX;
int vad_speech_pad_ms = 30;
float vad_samples_overlap = 0.1f;
bool use_gpu = false;
std::string fname_inp = {};
bool no_prints = false;
};
static void vad_print_usage(int /*argc*/, char ** argv, const cli_params & params) {
fprintf(stderr, "\n");
fprintf(stderr, "usage: %s [options] file\n", argv[0]);
fprintf(stderr, "supported audio formats: flac, mp3, ogg, wav\n");
fprintf(stderr, "\n");
fprintf(stderr, "options:\n");
fprintf(stderr, " -h, --help [default] show this help message and exit\n");
fprintf(stderr, " -f FNAME, --file FNAME [%-7s] input audio file path\n", "");
fprintf(stderr, " -t N, --threads N [%-7d] number of threads to use during computation\n", params.n_threads);
fprintf(stderr, " -ug, --use-gpu [%-7s] use GPU\n", params.use_gpu ? "true" : "false");
fprintf(stderr, " -vm FNAME, --vad-model FNAME [%-7s] VAD model path\n", params.vad_model.c_str());
fprintf(stderr, " -vt N, --vad-threshold N [%-7.2f] VAD threshold for speech recognition\n", params.vad_threshold);
fprintf(stderr, " -vspd N, --vad-min-speech-duration-ms N [%-7d] VAD min speech duration (0.0-1.0)\n", params.vad_min_speech_duration_ms);
fprintf(stderr, " -vsd N, --vad-min-silence-duration-ms N [%-7d] VAD min silence duration (to split segments)\n", params.vad_min_silence_duration_ms);
fprintf(stderr, " -vmsd N, --vad-max-speech-duration-s N [%-7s] VAD max speech duration (auto-split longer)\n", params.vad_max_speech_duration_s == FLT_MAX ?
std::string("FLT_MAX").c_str() :
std::to_string(params.vad_max_speech_duration_s).c_str());
fprintf(stderr, " -vp N, --vad-speech-pad-ms N [%-7d] VAD speech padding (extend segments)\n", params.vad_speech_pad_ms);
fprintf(stderr, " -vo N, --vad-samples-overlap N [%-7.2f] VAD samples overlap (seconds between segments)\n", params.vad_samples_overlap);
fprintf(stderr, " -np, --no-prints [%-7s] do not print anything other than the results\n", params.no_prints ? "true" : "false");
fprintf(stderr, "\n");
}
static char * requires_value_error(const std::string & arg) {
fprintf(stderr, "error: argument %s requires value\n", arg.c_str());
exit(0);
}
static bool vad_params_parse(int argc, char ** argv, cli_params & params) {
for (int i = 1; i < argc; i++) {
std::string arg = argv[i];
if (arg == "-h" || arg == "--help") {
vad_print_usage(argc, argv, params);
exit(0);
}
#define ARGV_NEXT (((i + 1) < argc) ? argv[++i] : requires_value_error(arg))
else if (arg == "-f" || arg == "--file") { params.fname_inp = ARGV_NEXT; }
else if (arg == "-t" || arg == "--threads") { params.n_threads = std::stoi(ARGV_NEXT); }
else if (arg == "-ug" || arg == "--use-gpu") { params.use_gpu = true; }
else if (arg == "-vm" || arg == "--vad-model") { params.vad_model = ARGV_NEXT; }
else if (arg == "-vt" || arg == "--vad-threshold") { params.vad_threshold = std::stof(ARGV_NEXT); }
else if (arg == "-vsd" || arg == "--vad-min-speech-duration-ms") { params.vad_min_speech_duration_ms = std::stoi(ARGV_NEXT); }
else if (arg == "-vsd" || arg == "--vad-min-silence-duration-ms") { params.vad_min_speech_duration_ms = std::stoi(ARGV_NEXT); }
else if (arg == "-vmsd" || arg == "--vad-max-speech-duration-s") { params.vad_max_speech_duration_s = std::stof(ARGV_NEXT); }
else if (arg == "-vp" || arg == "--vad-speech-pad-ms") { params.vad_speech_pad_ms = std::stoi(ARGV_NEXT); }
else if (arg == "-vo" || arg == "--vad-samples-overlap") { params.vad_samples_overlap = std::stof(ARGV_NEXT); }
else if (arg == "-np" || arg == "--no-prints") { params.no_prints = true; }
else {
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
vad_print_usage(argc, argv, params);
exit(0);
}
}
return true;
}
static void cb_log_disable(enum ggml_log_level , const char * , void * ) { }
int main(int argc, char ** argv) {
cli_params cli_params;
if (!vad_params_parse(argc, argv, cli_params)) {
vad_print_usage(argc, argv, cli_params);
return 1;
}
if (cli_params.no_prints) {
whisper_log_set(cb_log_disable, NULL);
}
// Load the input sample audio file.
std::vector<float> pcmf32;
std::vector<std::vector<float>> pcmf32s;
if (!read_audio_data(cli_params.fname_inp.c_str(), pcmf32, pcmf32s, false)) {
fprintf(stderr, "error: failed to read audio data from %s\n", cli_params.fname_inp.c_str());
return 2;
}
// Initialize the context which loads the VAD model.
struct whisper_vad_context_params ctx_params = whisper_vad_default_context_params();
ctx_params.n_threads = cli_params.n_threads;
ctx_params.use_gpu = cli_params.use_gpu;
struct whisper_vad_context * vctx = whisper_vad_init_from_file_with_params(
cli_params.vad_model.c_str(),
ctx_params);
// Detect speech in the input audio file.
if (!whisper_vad_detect_speech(vctx, pcmf32.data(), pcmf32.size())) {
fprintf(stderr, "error: failed to detect speech\n");
return 3;
}
// Get the the vad segements using the probabilities that have been computed
// previously and stored in the whisper_vad_context.
struct whisper_vad_params params = whisper_vad_default_params();
params.threshold = cli_params.vad_threshold;
params.min_speech_duration_ms = cli_params.vad_min_speech_duration_ms;
params.min_silence_duration_ms = cli_params.vad_min_silence_duration_ms;
params.max_speech_duration_s = cli_params.vad_max_speech_duration_s;
params.speech_pad_ms = cli_params.vad_speech_pad_ms;
params.samples_overlap = cli_params.vad_samples_overlap;
struct whisper_vad_segments * segments = whisper_vad_segments_from_probs(vctx, params);
printf("\n");
printf("Detected %d speech segments:\n", whisper_vad_segments_n_segments(segments));
for (int i = 0; i < whisper_vad_segments_n_segments(segments); ++i) {
printf("Speech segment %d: start = %.2f, end = %.2f\n", i,
whisper_vad_segments_get_segment_t0(segments, i),
whisper_vad_segments_get_segment_t1(segments, i));
}
printf("\n");
whisper_vad_free_segments(segments);
whisper_vad_free(vctx);
return 0;
}