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examples : add "command" tool (#171)

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This commit is contained in:
Georgi Gerganov 2022-11-25 19:06:56 +02:00
parent b8ce25dec1
commit bc88eb13c6
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9 changed files with 735 additions and 51 deletions
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1
.gitignore vendored
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@ -13,6 +13,7 @@ build-sanitize-thread/
main
stream
command
bench
sync.sh
compile_commands.json

5
Makefile
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@ -134,7 +134,7 @@ libwhisper.so: ggml.o whisper.o
$(CXX) $(CXXFLAGS) -shared -o libwhisper.so ggml.o whisper.o $(LDFLAGS)
clean:
rm -f *.o main stream bench libwhisper.a libwhisper.so
rm -f *.o main stream command bench libwhisper.a libwhisper.so
#
# Examples
@ -149,6 +149,9 @@ main: examples/main/main.cpp ggml.o whisper.o
stream: examples/stream/stream.cpp ggml.o whisper.o
$(CXX) $(CXXFLAGS) examples/stream/stream.cpp ggml.o whisper.o -o stream $(CC_SDL) $(LDFLAGS)
command: examples/command/command.cpp ggml.o whisper.o
$(CXX) $(CXXFLAGS) examples/command/command.cpp ggml.o whisper.o -o command $(CC_SDL) $(LDFLAGS)
bench: examples/bench/bench.cpp ggml.o whisper.o
$(CXX) $(CXXFLAGS) examples/bench/bench.cpp ggml.o whisper.o -o bench $(LDFLAGS)

51
README.md
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@ -98,26 +98,27 @@ c++ -I. -I./examples -O3 -std=c++11 -pthread examples/main/main.cpp whisper.o gg
usage: ./main [options] file0.wav file1.wav ...
options:
-h, --help show this help message and exit
-t N, --threads N number of threads to use during computation (default: 4)
-p N, --processors N number of processors to use during computation (default: 1)
-ot N, --offset-t N time offset in milliseconds (default: 0)
-on N, --offset-n N segment index offset (default: 0)
-mc N, --max-context N maximum number of text context tokens to store (default: max)
-ml N, --max-len N maximum segment length in characters (default: 0)
-wt N, --word-thold N word timestamp probability threshold (default: 0.010000)
-v, --verbose verbose output
--translate translate from source language to english
-otxt, --output-txt output result in a text file
-ovtt, --output-vtt output result in a vtt file
-osrt, --output-srt output result in a srt file
-owts, --output-words output script for generating karaoke video
-ps, --print_special print special tokens
-pc, --print_colors print colors
-nt, --no_timestamps do not print timestamps
-l LANG, --language LANG spoken language (default: en)
-m FNAME, --model FNAME model path (default: models/ggml-base.en.bin)
-f FNAME, --file FNAME input WAV file path
-h, --help [default] show this help message and exit
-t N, --threads N [4 ] number of threads to use during computation
-p N, --processors N [1 ] number of processors to use during computation
-ot N, --offset-t N [0 ] time offset in milliseconds
-on N, --offset-n N [0 ] segment index offset
-d N, --duration N [0 ] duration of audio to process in milliseconds
-mc N, --max-context N [-1 ] maximum number of text context tokens to store
-ml N, --max-len N [0 ] maximum segment length in characters
-wt N, --word-thold N [0.01 ] word timestamp probability threshold
-su, --speed-up [false ] speed up audio by x2 (reduced accuracy)
-tr, --translate [false ] translate from source language to english
-otxt, --output-txt [false ] output result in a text file
-ovtt, --output-vtt [false ] output result in a vtt file
-osrt, --output-srt [false ] output result in a srt file
-owts, --output-words [false ] output script for generating karaoke video
-ps, --print-special [false ] print special tokens
-pc, --print-colors [false ] print colors
-nt, --no-timestamps [true ] do not print timestamps
-l LANG, --language LANG [en ] spoken language
-m FNAME, --model FNAME [models/ggml-base.en.bin] model path
-f FNAME, --file FNAME [ ] input WAV file path
bash ./models/download-ggml-model.sh base.en
Downloading ggml model base.en ...
@ -149,13 +150,13 @@ whisper_model_load: n_text_layer = 6
whisper_model_load: n_mels = 80
whisper_model_load: f16 = 1
whisper_model_load: type = 2
whisper_model_load: mem_required = 670.00 MB
whisper_model_load: adding 1607 extra tokens
whisper_model_load: ggml ctx size = 140.60 MB
whisper_model_load: memory size = 22.83 MB
whisper_model_load: model size = 140.54 MB
whisper_model_load: mem_required = 506.00 MB
whisper_model_load: ggml ctx size = 140.60 MB
whisper_model_load: memory size = 22.83 MB
whisper_model_load: model size = 140.54 MB
system_info: n_threads = 4 / 10 | AVX2 = 0 | AVX512 = 0 | NEON = 1 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 |
system_info: n_threads = 4 / 10 | AVX = 0 | AVX2 = 0 | AVX512 = 0 | NEON = 1 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 |
main: processing 'samples/jfk.wav' (176000 samples, 11.0 sec), 4 threads, 1 processors, lang = en, task = transcribe, timestamps = 1 ...

1
examples/CMakeLists.txt
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@ -24,5 +24,6 @@ if (EMSCRIPTEN)
else()
add_subdirectory(main)
add_subdirectory(stream)
add_subdirectory(command)
add_subdirectory(bench)
endif()

7
examples/command/CMakeLists.txt Normal file
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@ -0,0 +1,7 @@
if (WHISPER_SUPPORT_SDL2)
# command
set(TARGET command)
add_executable(${TARGET} command.cpp)
target_include_directories(${TARGET} PRIVATE ${SDL2_INCLUDE_DIRS})
target_link_libraries(${TARGET} PRIVATE whisper ${SDL2_LIBRARIES} ${CMAKE_THREAD_LIBS_INIT})
endif ()

26
examples/command/README.md Normal file
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@ -0,0 +1,26 @@
# command
This is a basic Voice Assistant example that accepts voice commands from the microphone.
More info is available in [issue #171](https://github.com/ggerganov/whisper.cpp/issues/171).
```java
# Run with default arguments and small model
./command -m ./models/ggml-small.en.bin -t 8
# On Raspberry Pi, use tiny or base models + "-ac 768" for better performance
./bin/command -m ../models/ggml-tiny.en.bin -ac 768
```
## Building
The `command` tool depends on SDL2 library to capture audio from the microphone. You can build it like this:
```bash
# Install SDL2 on Linux
sudo apt-get install libsdl2-dev
# Install SDL2 on Mac OS
brew install sdl2
make command
```

646
examples/command/command.cpp Normal file
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@ -0,0 +1,646 @@
// Voice assistant example
//
// Speak short text commands to the microphone.
// This program will detect your voice command and convert them to text.
//
// ref: https://github.com/ggerganov/whisper.cpp/issues/171
//
#include "whisper.h"
#include <SDL.h>
#include <SDL_audio.h>
#include <cassert>
#include <cstdio>
#include <string>
#include <thread>
#include <vector>
#include <fstream>
#include <regex>
// command-line parameters
struct whisper_params {
int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
int32_t prompt_ms = 5000;
int32_t command_ms = 4000;
int32_t capture_id = -1;
int32_t max_tokens = 32;
int32_t audio_ctx = 0;
float vad_thold = 0.6f;
float freq_thold = 100.0f;
bool speed_up = false;
bool translate = false;
bool no_context = true;
bool print_special = false;
bool print_energy = false;
bool no_timestamps = true;
std::string language = "en";
std::string model = "models/ggml-base.en.bin";
std::string fname_out = "";
};
void whisper_print_usage(int argc, char ** argv, const whisper_params & params);
bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
for (int i = 1; i < argc; i++) {
std::string arg = argv[i];
if (arg == "-h" || arg == "--help") {
whisper_print_usage(argc, argv, params);
exit(0);
}
else if (arg == "-t" || arg == "--threads") { params.n_threads = std::stoi(argv[++i]); }
else if (arg == "-pms" || arg == "--prompt-ms") { params.prompt_ms = std::stoi(argv[++i]); }
else if (arg == "-cms" || arg == "--command-ms") { params.command_ms = std::stoi(argv[++i]); }
else if (arg == "-c" || arg == "--capture") { params.capture_id = std::stoi(argv[++i]); }
else if (arg == "-mt" || arg == "--max-tokens") { params.max_tokens = std::stoi(argv[++i]); }
else if (arg == "-ac" || arg == "--audio-ctx") { params.audio_ctx = std::stoi(argv[++i]); }
else if (arg == "-vth" || arg == "--vad-thold") { params.vad_thold = std::stof(argv[++i]); }
else if (arg == "-fth" || arg == "--freq-thold") { params.freq_thold = std::stof(argv[++i]); }
else if (arg == "-su" || arg == "--speed-up") { params.speed_up = true; }
else if (arg == "-tr" || arg == "--translate") { params.translate = true; }
else if (arg == "-ps" || arg == "--print-special") { params.print_special = true; }
else if (arg == "-pe" || arg == "--print-energy") { params.print_energy = true; }
else if (arg == "-l" || arg == "--language") { params.language = argv[++i]; }
else if (arg == "-m" || arg == "--model") { params.model = argv[++i]; }
else if (arg == "-f" || arg == "--file") { params.fname_out = argv[++i]; }
else {
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
whisper_print_usage(argc, argv, params);
exit(0);
}
}
return true;
}
void whisper_print_usage(int argc, char ** argv, const whisper_params & params) {
fprintf(stderr, "\n");
fprintf(stderr, "usage: %s [options]\n", argv[0]);
fprintf(stderr, "\n");
fprintf(stderr, "options:\n");
fprintf(stderr, " -h, --help [default] show this help message and exit\n");
fprintf(stderr, " -t N, --threads N [%-7d] number of threads to use during computation\n", params.n_threads);
fprintf(stderr, " -pms N, --prompt-ms N [%-7d] prompt duration in milliseconds\n", params.prompt_ms);
fprintf(stderr, " -cms N, --command-ms N [%-7d] command duration in milliseconds\n", params.command_ms);
fprintf(stderr, " -c ID, --capture ID [%-7d] capture device ID\n", params.capture_id);
fprintf(stderr, " -mt N, --max-tokens N [%-7d] maximum number of tokens per audio chunk\n", params.max_tokens);
fprintf(stderr, " -ac N, --audio-ctx N [%-7d] audio context size (0 - all)\n", params.audio_ctx);
fprintf(stderr, " -vth N, --vad-thold N [%-7.2f] voice activity detection threshold\n", params.vad_thold);
fprintf(stderr, " -fth N, --freq-thold N [%-7.2f] high-pass frequency cutoff\n", params.freq_thold);
fprintf(stderr, " -su, --speed-up [%-7s] speed up audio by x2 (reduced accuracy)\n", params.speed_up ? "true" : "false");
fprintf(stderr, " -tr, --translate [%-7s] translate from source language to english\n", params.translate ? "true" : "false");
fprintf(stderr, " -ps, --print-special [%-7s] print special tokens\n", params.print_special ? "true" : "false");
fprintf(stderr, " -pe, --print-energy [%-7s] print sound energy (for debugging)\n", params.print_energy ? "true" : "false");
fprintf(stderr, " -l LANG, --language LANG [%-7s] spoken language\n", params.language.c_str());
fprintf(stderr, " -m FNAME, --model FNAME [%-7s] model path\n", params.model.c_str());
fprintf(stderr, " -f FNAME, --file FNAME [%-7s] text output file name\n", params.fname_out.c_str());
fprintf(stderr, "\n");
}
//
// SDL Audio capture
//
class audio_async {
public:
audio_async(int len_ms) {
m_len_ms = len_ms;
}
bool init(int capture_id, int sample_rate);
// start capturing audio via the provided SDL callback
// keep last len_ms seconds of audio in a circular buffer
bool resume();
bool pause();
bool clear();
// callback to be called by SDL
void callback(uint8_t * stream, int len);
// get audio data from the circular buffer
void get(int ms, std::vector<float> & audio);
private:
SDL_AudioDeviceID m_dev_id_in = 0;
int m_len_ms = 0;
int m_sample_rate = 0;
bool m_running = false;
std::mutex m_mutex;
std::vector<float> m_audio;
std::vector<float> m_audio_new;
size_t m_audio_pos = 0;
size_t m_audio_len = 0;
};
bool audio_async::init(int capture_id, int sample_rate) {
SDL_LogSetPriority(SDL_LOG_CATEGORY_APPLICATION, SDL_LOG_PRIORITY_INFO);
if (SDL_Init(SDL_INIT_AUDIO) < 0) {
SDL_LogError(SDL_LOG_CATEGORY_APPLICATION, "Couldn't initialize SDL: %s\n", SDL_GetError());
return false;
}
SDL_SetHintWithPriority(SDL_HINT_AUDIO_RESAMPLING_MODE, "medium", SDL_HINT_OVERRIDE);
{
int nDevices = SDL_GetNumAudioDevices(SDL_TRUE);
fprintf(stderr, "%s: found %d capture devices:\n", __func__, nDevices);
for (int i = 0; i < nDevices; i++) {
fprintf(stderr, "%s: - Capture device #%d: '%s'\n", __func__, i, SDL_GetAudioDeviceName(i, SDL_TRUE));
}
}
SDL_AudioSpec capture_spec_requested;
SDL_AudioSpec capture_spec_obtained;
SDL_zero(capture_spec_requested);
SDL_zero(capture_spec_obtained);
capture_spec_requested.freq = sample_rate;
capture_spec_requested.format = AUDIO_F32;
capture_spec_requested.channels = 1;
capture_spec_requested.samples = 1024;
capture_spec_requested.callback = [](void * userdata, uint8_t * stream, int len) {
audio_async * audio = (audio_async *) userdata;
audio->callback(stream, len);
};
capture_spec_requested.userdata = this;
if (capture_id >= 0) {
fprintf(stderr, "%s: attempt to open capture device %d : '%s' ...\n", __func__, capture_id, SDL_GetAudioDeviceName(capture_id, SDL_TRUE));
m_dev_id_in = SDL_OpenAudioDevice(SDL_GetAudioDeviceName(capture_id, SDL_TRUE), SDL_TRUE, &capture_spec_requested, &capture_spec_obtained, 0);
} else {
fprintf(stderr, "%s: attempt to open default capture device ...\n", __func__);
m_dev_id_in = SDL_OpenAudioDevice(nullptr, SDL_TRUE, &capture_spec_requested, &capture_spec_obtained, 0);
}
if (!m_dev_id_in) {
fprintf(stderr, "%s: couldn't open an audio device for capture: %s!\n", __func__, SDL_GetError());
m_dev_id_in = 0;
return false;
} else {
fprintf(stderr, "%s: obtained spec for input device (SDL Id = %d):\n", __func__, m_dev_id_in);
fprintf(stderr, "%s: - sample rate: %d\n", __func__, capture_spec_obtained.freq);
fprintf(stderr, "%s: - format: %d (required: %d)\n", __func__, capture_spec_obtained.format,
capture_spec_requested.format);
fprintf(stderr, "%s: - channels: %d (required: %d)\n", __func__, capture_spec_obtained.channels,
capture_spec_requested.channels);
fprintf(stderr, "%s: - samples per frame: %d\n", __func__, capture_spec_obtained.samples);
}
m_sample_rate = capture_spec_obtained.freq;
m_audio.resize((m_sample_rate*m_len_ms)/1000);
return true;
}
bool audio_async::resume() {
if (!m_dev_id_in) {
fprintf(stderr, "%s: no audio device to resume!\n", __func__);
return false;
}
if (m_running) {
fprintf(stderr, "%s: already running!\n", __func__);
return false;
}
SDL_PauseAudioDevice(m_dev_id_in, 0);
m_running = true;
return true;
}
bool audio_async::pause() {
if (!m_dev_id_in) {
fprintf(stderr, "%s: no audio device to pause!\n", __func__);
return false;
}
if (!m_running) {
fprintf(stderr, "%s: already paused!\n", __func__);
return false;
}
SDL_PauseAudioDevice(m_dev_id_in, 1);
m_running = false;
return true;
}
bool audio_async::clear() {
if (!m_dev_id_in) {
fprintf(stderr, "%s: no audio device to clear!\n", __func__);
return false;
}
if (!m_running) {
fprintf(stderr, "%s: not running!\n", __func__);
return false;
}
{
std::lock_guard<std::mutex> lock(m_mutex);
m_audio_pos = 0;
m_audio_len = 0;
}
return true;
}
// callback to be called by SDL
void audio_async::callback(uint8_t * stream, int len) {
if (!m_running) {
return;
}
const size_t n_samples = len / sizeof(float);
m_audio_new.resize(n_samples);
memcpy(m_audio_new.data(), stream, n_samples * sizeof(float));
//fprintf(stderr, "%s: %zu samples, pos %zu, len %zu\n", __func__, n_samples, m_audio_pos, m_audio_len);
{
std::lock_guard<std::mutex> lock(m_mutex);
if (m_audio_pos + n_samples > m_audio.size()) {
const size_t n0 = m_audio.size() - m_audio_pos;
memcpy(&m_audio[m_audio_pos], stream, n0 * sizeof(float));
memcpy(&m_audio[0], &stream[n0], (n_samples - n0) * sizeof(float));
m_audio_pos = (m_audio_pos + n_samples) % m_audio.size();
m_audio_len = m_audio.size();
} else {
memcpy(&m_audio[m_audio_pos], stream, n_samples * sizeof(float));
m_audio_pos = (m_audio_pos + n_samples) % m_audio.size();
m_audio_len = std::min(m_audio_len + n_samples, m_audio.size());
}
}
}
void audio_async::get(int ms, std::vector<float> & result) {
if (!m_dev_id_in) {
fprintf(stderr, "%s: no audio device to get audio from!\n", __func__);
return;
}
if (!m_running) {
fprintf(stderr, "%s: not running!\n", __func__);
return;
}
result.clear();
{
std::lock_guard<std::mutex> lock(m_mutex);
if (ms <= 0) {
ms = m_len_ms;
}
size_t n_samples = (m_sample_rate * ms) / 1000;
if (n_samples > m_audio_len) {
n_samples = m_audio_len;
}
result.resize(n_samples);
int s0 = m_audio_pos - n_samples;
if (s0 < 0) {
s0 += m_audio.size();
}
if (s0 + n_samples > m_audio.size()) {
const size_t n0 = m_audio.size() - s0;
memcpy(result.data(), &m_audio[s0], n0 * sizeof(float));
memcpy(&result[n0], &m_audio[0], (n_samples - n0) * sizeof(float));
} else {
memcpy(result.data(), &m_audio[s0], n_samples * sizeof(float));
}
}
}
///////////////////////////
std::string trim(const std::string & s) {
std::regex e("^\\s+|\\s+$");
return std::regex_replace(s, e, "");
}
void high_pass_filter(std::vector<float> & data, float cutoff, float sample_rate) {
const float rc = 1.0f / (2.0f * M_PI * cutoff);
const float dt = 1.0f / sample_rate;
const float alpha = dt / (rc + dt);
float y = data[0];
for (size_t i = 1; i < data.size(); i++) {
y = alpha * (y + data[i] - data[i - 1]);
data[i] = y;
}
}
bool vad_simple(std::vector<float> & pcmf32, int sample_rate, int last_ms, float vad_thold, float freq_thold, bool verbose) {
const int n_samples = pcmf32.size();
const int n_samples_last = (sample_rate * last_ms) / 1000;
if (n_samples_last >= n_samples) {
// not enough samples - assume no speech
return false;
}
if (freq_thold > 0.0f) {
high_pass_filter(pcmf32, freq_thold, sample_rate);
}
float energy_all = 0.0f;
float energy_last = 0.0f;
for (size_t i = 0; i < n_samples; i++) {
energy_all += fabsf(pcmf32[i]);
if (i >= n_samples - n_samples_last) {
energy_last += fabsf(pcmf32[i]);
}
}
energy_all /= n_samples;
energy_last /= n_samples_last;
if (verbose) {
fprintf(stderr, "%s: energy_all: %f, energy_last: %f, vad_thold: %f, freq_thold: %f\n", __func__, energy_all, energy_last, vad_thold, freq_thold);
}
if (energy_last > vad_thold*energy_all) {
return false;
}
return true;
}
std::string transcribe(whisper_context * ctx, const whisper_params & params, const std::vector<float> & pcmf32, float & prob, int64_t & t_ms) {
const auto t_start = std::chrono::high_resolution_clock::now();
prob = 0.0f;
t_ms = 0;
whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
wparams.print_progress = false;
wparams.print_special = params.print_special;
wparams.print_realtime = false;
wparams.print_timestamps = !params.no_timestamps;
wparams.translate = params.translate;
wparams.no_context = true;
wparams.single_segment = true;
wparams.max_tokens = params.max_tokens;
wparams.language = params.language.c_str();
wparams.n_threads = params.n_threads;
wparams.audio_ctx = params.audio_ctx;
wparams.speed_up = params.speed_up;
if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
return "";
}
int prob_n = 0;
std::string result;
const int n_segments = whisper_full_n_segments(ctx);
for (int i = 0; i < n_segments; ++i) {
const char * text = whisper_full_get_segment_text(ctx, i);
result += text;
const int n_tokens = whisper_full_n_tokens(ctx, i);
for (int j = 0; j < n_tokens; ++j) {
const auto token = whisper_full_get_token_data(ctx, i, j);
prob += token.p;
++prob_n;
}
}
if (prob_n > 0) {
prob /= prob_n;
}
const auto t_end = std::chrono::high_resolution_clock::now();
t_ms = std::chrono::duration_cast<std::chrono::milliseconds>(t_end - t_start).count();
return result;
}
// compute similarity between two strings using Levenshtein distance
float similarity(const std::string & s0, const std::string & s1) {
const size_t len0 = s0.size() + 1;
const size_t len1 = s1.size() + 1;
std::vector<int> col(len1, 0);
std::vector<int> prevCol(len1, 0);
for (size_t i = 0; i < len1; i++) {
prevCol[i] = i;
}
for (size_t i = 0; i < len0; i++) {
col[0] = i;
for (size_t j = 1; j < len1; j++) {
col[j] = std::min(std::min(1 + col[j - 1], 1 + prevCol[j]), prevCol[j - 1] + (s0[i - 1] == s1[j - 1] ? 0 : 1));
}
col.swap(prevCol);
}
const float dist = prevCol[len1 - 1];
return 1.0f - (dist / std::max(s0.size(), s1.size()));
}
int main(int argc, char ** argv) {
whisper_params params;
if (whisper_params_parse(argc, argv, params) == false) {
return 1;
}
if (whisper_lang_id(params.language.c_str()) == -1) {
fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
whisper_print_usage(argc, argv, params);
exit(0);
}
// whisper init
struct whisper_context * ctx = whisper_init(params.model.c_str());
// print some info about the processing
{
fprintf(stderr, "\n");
if (!whisper_is_multilingual(ctx)) {
if (params.language != "en" || params.translate) {
params.language = "en";
params.translate = false;
fprintf(stderr, "%s: WARNING: model is not multilingual, ignoring language and translation options\n", __func__);
}
}
fprintf(stderr, "%s: processing, %d threads, lang = %s, task = %s, timestamps = %d ...\n",
__func__,
params.n_threads,
params.language.c_str(),
params.translate ? "translate" : "transcribe",
params.no_timestamps ? 0 : 1);
fprintf(stderr, "\n");
}
// init audio
audio_async audio(30*1000);
if (!audio.init(params.capture_id, WHISPER_SAMPLE_RATE)) {
fprintf(stderr, "%s: audio.init() failed!\n", __func__);
return 1;
}
audio.resume();
bool is_running = true;
bool have_prompt = false;
bool ask_prompt = true;
float prob0 = 0.0f;
float prob = 0.0f;
std::vector<float> pcmf32_cur;
std::vector<float> pcmf32_prompt;
const std::string k_prompt = "Ok Whisper, start listening for commands.";
// main loop
while (is_running) {
// handle Ctrl + C
{
SDL_Event event;
while (SDL_PollEvent(&event)) {
switch (event.type) {
case SDL_QUIT:
{
is_running = false;
} break;
default:
break;
}
}
if (!is_running) {
break;
}
}
// delay
std::this_thread::sleep_for(std::chrono::milliseconds(100));
if (ask_prompt) {
fprintf(stdout, "\n");
fprintf(stdout, "%s: Say the following phrase: '%s'\n", __func__, k_prompt.c_str());
fprintf(stdout, "\n");
ask_prompt = false;
}
int64_t t_ms = 0;
{
audio.get(2000, pcmf32_cur);
if (vad_simple(pcmf32_cur, WHISPER_SAMPLE_RATE, 1000, params.vad_thold, params.freq_thold, params.print_energy)) {
fprintf(stdout, "%s: Speech detected!\n", __func__);
if (!have_prompt) {
audio.get(params.prompt_ms, pcmf32_cur);
const auto txt = ::trim(::transcribe(ctx, params, pcmf32_cur, prob0, t_ms));
fprintf(stdout, "%s: Heard '%s', (prob = %6.3f, t = %d ms)\n", __func__, txt.c_str(), prob0, (int) t_ms);
const float sim = similarity(txt, k_prompt);
if (txt.length() < 0.8*k_prompt.length() || txt.length() > 1.2*k_prompt.length() || sim < 0.8f) {
fprintf(stdout, "%s: WARNING: prompt not recognized, try again\n", __func__);
ask_prompt = true;
} else {
fprintf(stdout, "\n");
fprintf(stdout, "%s: The prompt has been recognized!\n", __func__);
fprintf(stdout, "%s: Waiting for voice commands ...\n", __func__);
fprintf(stdout, "\n");
// save the audio for the prompt
pcmf32_prompt = pcmf32_cur;
have_prompt = true;
}
} else {
audio.get(params.command_ms, pcmf32_cur);
// prepend the prompt audio
pcmf32_cur.insert(pcmf32_cur.begin(), pcmf32_prompt.begin(), pcmf32_prompt.end());
const auto txt = ::trim(::transcribe(ctx, params, pcmf32_cur, prob, t_ms));
printf("prob0 = %6.3f, prob = %6.3f, t = %d ms\n", prob0, prob, (int) t_ms);
prob = 100.0f*(prob - prob0);
//fprintf(stdout, "%s: heard '%s'\n", __func__, txt.c_str());
// find the prompt in the text
float best_sim = 0.0f;
size_t best_len = 0;
for (int n = 0.8*k_prompt.size(); n <= 1.2*k_prompt.size(); ++n) {
const auto prompt = txt.substr(0, n);
const float sim = similarity(prompt, k_prompt);
//fprintf(stderr, "%s: prompt = '%s', sim = %f\n", __func__, prompt.c_str(), sim);
if (sim > best_sim) {
best_sim = sim;
best_len = n;
}
}
const std::string command = ::trim(txt.substr(best_len));
fprintf(stdout, "%s: Command '%s', (prob = %6.3f, t = %d ms)\n", __func__, command.c_str(), prob, (int) t_ms);
fprintf(stdout, "\n");
}
audio.clear();
}
}
}
audio.pause();
whisper_print_timings(ctx);
whisper_free(ctx);
return 0;
}

47
examples/main/README.md
View File

@ -6,29 +6,28 @@ It can be used as a reference for using the `whisper.cpp` library in other proje
```
./main -h
usage: ./bin/main [options] file0.wav file1.wav ...
-h, --help show this help message and exit
-s SEED, --seed SEED RNG seed (default: -1)
-t N, --threads N number of threads to use during computation (default: 4)
-p N, --processors N number of processors to use during computation (default: 1)
-ot N, --offset-t N time offset in milliseconds (default: 0)
-on N, --offset-n N segment index offset (default: 0)
-mc N, --max-context N maximum number of text context tokens to store (default: max)
-ml N, --max-len N maximum segment length in characters (default: 0)
-wt N, --word-thold N word timestamp probability threshold (default: 0.010000)
-v, --verbose verbose output
--translate translate from source language to english
-otxt, --output-txt output result in a text file
-ovtt, --output-vtt output result in a vtt file
-osrt, --output-srt output result in a srt file
-owts, --output-words output script for generating karaoke video
-ps, --print_special print special tokens
-pc, --print_colors print colors
-nt, --no_timestamps do not print timestamps
-l LANG, --language LANG spoken language (default: en)
-m FNAME, --model FNAME model path (default: models/ggml-base.en.bin)
-f FNAME, --file FNAME input WAV file path
-h, --help show this help message and exit
usage: ./main [options] file0.wav file1.wav ...
options:
-h, --help [default] show this help message and exit
-t N, --threads N [4 ] number of threads to use during computation
-p N, --processors N [1 ] number of processors to use during computation
-ot N, --offset-t N [0 ] time offset in milliseconds
-on N, --offset-n N [0 ] segment index offset
-d N, --duration N [0 ] duration of audio to process in milliseconds
-mc N, --max-context N [-1 ] maximum number of text context tokens to store
-ml N, --max-len N [0 ] maximum segment length in characters
-wt N, --word-thold N [0.01 ] word timestamp probability threshold
-su, --speed-up [false ] speed up audio by x2 (reduced accuracy)
-tr, --translate [false ] translate from source language to english
-otxt, --output-txt [false ] output result in a text file
-ovtt, --output-vtt [false ] output result in a vtt file
-osrt, --output-srt [false ] output result in a srt file
-owts, --output-words [false ] output script for generating karaoke video
-ps, --print-special [false ] print special tokens
-pc, --print-colors [false ] print colors
-nt, --no-timestamps [true ] do not print timestamps
-l LANG, --language LANG [en ] spoken language
-m FNAME, --model FNAME [models/ggml-base.en.bin] model path
-f FNAME, --file FNAME [ ] input WAV file path
```

2
examples/main/main.cpp
View File

@ -132,7 +132,7 @@ void whisper_print_usage(int argc, char ** argv, const whisper_params & params)
fprintf(stderr, " -d N, --duration N [%-7d] duration of audio to process in milliseconds\n", params.duration_ms);
fprintf(stderr, " -mc N, --max-context N [%-7d] maximum number of text context tokens to store\n", params.max_context);
fprintf(stderr, " -ml N, --max-len N [%-7d] maximum segment length in characters\n", params.max_len);
fprintf(stderr, " -wt N, --word-thold N [%-7f] word timestamp probability threshold\n", params.word_thold);
fprintf(stderr, " -wt N, --word-thold N [%-7.2f] word timestamp probability threshold\n", params.word_thold);
fprintf(stderr, " -su, --speed-up [%-7s] speed up audio by x2 (reduced accuracy)\n", params.speed_up ? "true" : "false");
fprintf(stderr, " -tr, --translate [%-7s] translate from source language to english\n", params.translate ? "true" : "false");
fprintf(stderr, " -otxt, --output-txt [%-7s] output result in a text file\n", params.output_txt ? "true" : "false");