// sherpa-onnx/csrc/sherpa-onnx.cc // // Copyright (c) 2022-2023 Xiaomi Corporation #include #include // NOLINT #include #include #include #include #include "sherpa-onnx/csrc/online-recognizer.h" #include "sherpa-onnx/csrc/online-stream.h" #include "sherpa-onnx/csrc/parse-options.h" #include "sherpa-onnx/csrc/symbol-table.h" #include "sherpa-onnx/csrc/wave-reader.h" typedef struct { std::unique_ptr online_stream; float duration; float elapsed_seconds; } Stream; int main(int32_t argc, char *argv[]) { const char *kUsageMessage = R"usage( Usage: ./bin/sherpa-onnx \ --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 \ --decoding-method=greedy_search \ /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 decoding_method: greedy_search (default), modified_beam_search. 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::OnlineRecognizerConfig 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::OnlineRecognizer recognizer(config); std::vector ss; const auto begin = std::chrono::steady_clock::now(); std::vector durations; 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; } const float duration = samples.size() / static_cast(sampling_rate); auto s = recognizer.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), duration, 0}); } std::vector ready_streams; for (;;) { ready_streams.clear(); for (auto &s : ss) { const auto p_ss = s.online_stream.get(); if (recognizer.IsReady(p_ss)) { ready_streams.push_back(p_ss); } else if (s.elapsed_seconds == 0) { const auto end = std::chrono::steady_clock::now(); const float elapsed_seconds = std::chrono::duration_cast(end - begin) .count() / 1000.; s.elapsed_seconds = elapsed_seconds; } } if (ready_streams.empty()) { break; } recognizer.DecodeStreams(ready_streams.data(), ready_streams.size()); } std::ostringstream os; for (int32_t i = 1; i <= po.NumArgs(); ++i) { const auto &s = ss[i - 1]; const float rtf = s.elapsed_seconds / s.duration; os << po.GetArg(i) << "\n"; os << std::setprecision(2) << "Elapsed seconds: " << s.elapsed_seconds << ", Real time factor (RTF): " << rtf << "\n"; const auto r = recognizer.GetResult(s.online_stream.get()); os << r.text << "\n"; os << r.AsJsonString() << "\n\n"; } std::cerr << os.str(); return 0; }