149 lines
4.1 KiB
C++
149 lines
4.1 KiB
C++
// sherpa-onnx/csrc/sherpa-onnx-keyword-spotter-microphone.cc
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//
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// Copyright (c) 2024 Xiaomi Corporation
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#include <signal.h>
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#include <stdio.h>
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#include <stdlib.h>
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#include <algorithm>
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#include "portaudio.h" // NOLINT
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#include "sherpa-onnx/csrc/display.h"
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#include "sherpa-onnx/csrc/microphone.h"
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#include "sherpa-onnx/csrc/keyword-spotter.h"
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bool stop = false;
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static int32_t RecordCallback(const void *input_buffer,
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void * /*output_buffer*/,
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unsigned long frames_per_buffer, // NOLINT
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const PaStreamCallbackTimeInfo * /*time_info*/,
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PaStreamCallbackFlags /*status_flags*/,
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void *user_data) {
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auto stream = reinterpret_cast<sherpa_onnx::OnlineStream *>(user_data);
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stream->AcceptWaveform(16000, reinterpret_cast<const float *>(input_buffer),
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frames_per_buffer);
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return stop ? paComplete : paContinue;
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}
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static void Handler(int32_t sig) {
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stop = true;
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fprintf(stderr, "\nCaught Ctrl + C. Exiting...\n");
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}
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int32_t main(int32_t argc, char *argv[]) {
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signal(SIGINT, Handler);
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const char *kUsageMessage = R"usage(
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This program uses streaming models with microphone for keyword spotting.
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Usage:
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./bin/sherpa-onnx-keyword-spotter-microphone \
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--tokens=/path/to/tokens.txt \
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--encoder=/path/to/encoder.onnx \
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--decoder=/path/to/decoder.onnx \
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--joiner=/path/to/joiner.onnx \
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--provider=cpu \
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--num-threads=1 \
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--keywords-file=keywords.txt
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Please refer to
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https://k2-fsa.github.io/sherpa/onnx/kws/pretrained_models/index.html
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for a list of pre-trained models to download.
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)usage";
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sherpa_onnx::ParseOptions po(kUsageMessage);
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sherpa_onnx::KeywordSpotterConfig config;
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config.Register(&po);
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po.Read(argc, argv);
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if (po.NumArgs() != 0) {
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po.PrintUsage();
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exit(EXIT_FAILURE);
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}
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fprintf(stderr, "%s\n", config.ToString().c_str());
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if (!config.Validate()) {
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fprintf(stderr, "Errors in config!\n");
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return -1;
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}
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sherpa_onnx::KeywordSpotter spotter(config);
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auto s = spotter.CreateStream();
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sherpa_onnx::Microphone mic;
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PaDeviceIndex num_devices = Pa_GetDeviceCount();
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fprintf(stderr, "Num devices: %d\n", num_devices);
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PaStreamParameters param;
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param.device = Pa_GetDefaultInputDevice();
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if (param.device == paNoDevice) {
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fprintf(stderr, "No default input device found\n");
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exit(EXIT_FAILURE);
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}
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fprintf(stderr, "Use default device: %d\n", param.device);
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const PaDeviceInfo *info = Pa_GetDeviceInfo(param.device);
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fprintf(stderr, " Name: %s\n", info->name);
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fprintf(stderr, " Max input channels: %d\n", info->maxInputChannels);
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param.channelCount = 1;
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param.sampleFormat = paFloat32;
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param.suggestedLatency = info->defaultLowInputLatency;
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param.hostApiSpecificStreamInfo = nullptr;
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float sample_rate = 16000;
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PaStream *stream;
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PaError err =
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Pa_OpenStream(&stream, ¶m, nullptr, /* &outputParameters, */
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sample_rate,
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0, // frames per buffer
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paClipOff, // we won't output out of range samples
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// so don't bother clipping them
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RecordCallback, s.get());
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if (err != paNoError) {
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fprintf(stderr, "portaudio error: %s\n", Pa_GetErrorText(err));
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exit(EXIT_FAILURE);
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}
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err = Pa_StartStream(stream);
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fprintf(stderr, "Started\n");
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if (err != paNoError) {
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fprintf(stderr, "portaudio error: %s\n", Pa_GetErrorText(err));
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exit(EXIT_FAILURE);
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}
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int32_t keyword_index = 0;
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sherpa_onnx::Display display;
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while (!stop) {
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while (spotter.IsReady(s.get())) {
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spotter.DecodeStream(s.get());
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}
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const auto r = spotter.GetResult(s.get());
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if (!r.keyword.empty()) {
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display.Print(keyword_index, r.AsJsonString());
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fflush(stderr);
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keyword_index++;
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}
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Pa_Sleep(20); // sleep for 20ms
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}
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err = Pa_CloseStream(stream);
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if (err != paNoError) {
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fprintf(stderr, "portaudio error: %s\n", Pa_GetErrorText(err));
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exit(EXIT_FAILURE);
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}
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return 0;
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}
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