// sherpa-onnx/csrc/sherpa-onnx-keyword-spotter.cc // // Copyright (c) 2023-2024 Xiaomi Corporation #include #include #include #include #include #include "sherpa-onnx/csrc/keyword-spotter.h" #include "sherpa-onnx/csrc/online-stream.h" #include "sherpa-onnx/csrc/parse-options.h" #include "sherpa-onnx/csrc/wave-reader.h" typedef struct { std::unique_ptr online_stream; std::string filename; } Stream; int main(int32_t argc, char *argv[]) { const char *kUsageMessage = R"usage( Usage: (1) Streaming transducer ./bin/sherpa-onnx-keyword-spotter \ --tokens=/path/to/tokens.txt \ --encoder=/path/to/encoder.onnx \ --decoder=/path/to/decoder.onnx \ --joiner=/path/to/joiner.onnx \ --provider=cpu \ --num-threads=2 \ --keywords-file=keywords.txt \ /path/to/foo.wav [bar.wav foobar.wav ...] Note: It supports decoding multiple files in batches Default value for num_threads is 2. Valid values for provider: cpu (default), cuda, coreml. foo.wav should be of single channel, 16-bit PCM encoded wave file; its sampling rate can be arbitrary and does not need to be 16kHz. Please refer to https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html for a list of pre-trained models to download. )usage"; sherpa_onnx::ParseOptions po(kUsageMessage); sherpa_onnx::KeywordSpotterConfig config; config.Register(&po); po.Read(argc, argv); if (po.NumArgs() < 1) { po.PrintUsage(); exit(EXIT_FAILURE); } fprintf(stderr, "%s\n", config.ToString().c_str()); if (!config.Validate()) { fprintf(stderr, "Errors in config!\n"); return -1; } sherpa_onnx::KeywordSpotter keyword_spotter(config); std::vector ss; for (int32_t i = 1; i <= po.NumArgs(); ++i) { const std::string wav_filename = po.GetArg(i); int32_t sampling_rate = -1; bool is_ok = false; const std::vector samples = sherpa_onnx::ReadWave(wav_filename, &sampling_rate, &is_ok); if (!is_ok) { fprintf(stderr, "Failed to read '%s'\n", wav_filename.c_str()); return -1; } auto s = keyword_spotter.CreateStream(); s->AcceptWaveform(sampling_rate, samples.data(), samples.size()); std::vector tail_paddings(static_cast(0.8 * sampling_rate)); // Note: We can call AcceptWaveform() multiple times. s->AcceptWaveform(sampling_rate, tail_paddings.data(), tail_paddings.size()); // Call InputFinished() to indicate that no audio samples are available s->InputFinished(); ss.push_back({std::move(s), wav_filename}); } std::vector ready_streams; for (;;) { ready_streams.clear(); for (auto &s : ss) { const auto p_ss = s.online_stream.get(); if (keyword_spotter.IsReady(p_ss)) { ready_streams.push_back(p_ss); } std::ostringstream os; const auto r = keyword_spotter.GetResult(p_ss); if (!r.keyword.empty()) { os << s.filename << "\n"; os << r.AsJsonString() << "\n\n"; fprintf(stderr, "%s", os.str().c_str()); } } if (ready_streams.empty()) { break; } keyword_spotter.DecodeStreams(ready_streams.data(), ready_streams.size()); } return 0; }