121 lines
3.4 KiB
C++
121 lines
3.4 KiB
C++
// sherpa-onnx/csrc/sherpa-onnx-offline.cc
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//
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// Copyright (c) 2022-2023 Xiaomi Corporation
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#include <stdio.h>
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#include <chrono> // NOLINT
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#include <string>
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#include <vector>
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#include "sherpa-onnx/csrc/offline-recognizer.h"
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#include "sherpa-onnx/csrc/parse-options.h"
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#include "sherpa-onnx/csrc/wave-reader.h"
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int main(int32_t argc, char *argv[]) {
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const char *kUsageMessage = R"usage(
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Usage:
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(1) Transducer from icefall
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./bin/sherpa-onnx-offline \
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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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--num-threads=2 \
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--decoding-method=greedy_search \
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/path/to/foo.wav [bar.wav foobar.wav ...]
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(2) Paraformer from FunASR
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./bin/sherpa-onnx-offline \
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--tokens=/path/to/tokens.txt \
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--paraformer=/path/to/model.onnx \
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--num-threads=2 \
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--decoding-method=greedy_search \
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/path/to/foo.wav [bar.wav foobar.wav ...]
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Note: It supports decoding multiple files in batches
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Default value for num_threads is 2.
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Valid values for decoding_method: greedy_search.
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foo.wav should be of single channel, 16-bit PCM encoded wave file; its
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sampling rate can be arbitrary and does not need to be 16kHz.
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Please refer to
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https://k2-fsa.github.io/sherpa/onnx/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::OfflineRecognizerConfig config;
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config.Register(&po);
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po.Read(argc, argv);
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if (po.NumArgs() < 1) {
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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::OfflineRecognizer recognizer(config);
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auto begin = std::chrono::steady_clock::now();
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fprintf(stderr, "Started\n");
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std::vector<std::unique_ptr<sherpa_onnx::OfflineStream>> ss;
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std::vector<sherpa_onnx::OfflineStream *> ss_pointers;
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float duration = 0;
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for (int32_t i = 1; i <= po.NumArgs(); ++i) {
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std::string wav_filename = po.GetArg(i);
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int32_t sampling_rate = -1;
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bool is_ok = false;
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std::vector<float> samples =
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sherpa_onnx::ReadWave(wav_filename, &sampling_rate, &is_ok);
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if (!is_ok) {
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fprintf(stderr, "Failed to read %s\n", wav_filename.c_str());
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return -1;
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}
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duration += samples.size() / static_cast<float>(sampling_rate);
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auto s = recognizer.CreateStream();
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s->AcceptWaveform(sampling_rate, samples.data(), samples.size());
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ss.push_back(std::move(s));
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ss_pointers.push_back(ss.back().get());
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}
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recognizer.DecodeStreams(ss_pointers.data(), ss_pointers.size());
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auto end = std::chrono::steady_clock::now();
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fprintf(stderr, "Done!\n\n");
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for (int32_t i = 1; i <= po.NumArgs(); ++i) {
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fprintf(stderr, "%s\n%s\n----\n", po.GetArg(i).c_str(),
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ss[i - 1]->GetResult().text.c_str());
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}
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float elapsed_seconds =
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std::chrono::duration_cast<std::chrono::milliseconds>(end - begin)
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.count() /
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1000.;
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fprintf(stderr, "num threads: %d\n", config.model_config.num_threads);
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fprintf(stderr, "decoding method: %s\n", config.decoding_method.c_str());
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fprintf(stderr, "Elapsed seconds: %.3f s\n", elapsed_seconds);
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float rtf = elapsed_seconds / duration;
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fprintf(stderr, "Real time factor (RTF): %.3f / %.3f = %.3f\n",
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elapsed_seconds, duration, rtf);
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return 0;
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}
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