79c2ce5dd4
* Refactor online recognizer. Make it easier to support other streaming models. Note that it is a breaking change for the Python API. `sherpa_onnx.OnlineRecognizer()` used before should be replaced by `sherpa_onnx.OnlineRecognizer.from_transducer()`.
141 lines
3.4 KiB
C++
141 lines
3.4 KiB
C++
// sherpa-onnx/csrc/sherpa-onnx-alsa.cc
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//
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// Copyright (c) 2022-2023 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 <cctype> // std::tolower
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#include <cstdint>
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#include "sherpa-onnx/csrc/alsa.h"
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#include "sherpa-onnx/csrc/display.h"
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#include "sherpa-onnx/csrc/online-recognizer.h"
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#include "sherpa-onnx/csrc/parse-options.h"
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bool stop = false;
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static void Handler(int 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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int 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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Usage:
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./bin/sherpa-onnx-alsa \
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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=2 \
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--decoding-method=greedy_search \
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device_name \
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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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The device name specifies which microphone to use in case there are several
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on you system. You can use
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arecord -l
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to find all available microphones on your computer. For instance, if it outputs
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**** List of CAPTURE Hardware Devices ****
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card 3: UACDemoV10 [UACDemoV1.0], device 0: USB Audio [USB Audio]
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Subdevices: 1/1
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Subdevice #0: subdevice #0
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and if you want to select card 3 and the device 0 on that card, please use:
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hw:3,0
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or
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plughw:3,0
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as the device_name.
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)usage";
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sherpa_onnx::ParseOptions po(kUsageMessage);
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sherpa_onnx::OnlineRecognizerConfig 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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fprintf(stderr, "Please provide only 1 argument: the device name\n");
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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::OnlineRecognizer recognizer(config);
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int32_t expected_sample_rate = config.feat_config.sampling_rate;
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std::string device_name = po.GetArg(1);
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sherpa_onnx::Alsa alsa(device_name.c_str());
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fprintf(stderr, "Use recording device: %s\n", device_name.c_str());
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if (alsa.GetExpectedSampleRate() != expected_sample_rate) {
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fprintf(stderr, "sample rate: %d != %d\n", alsa.GetExpectedSampleRate(),
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expected_sample_rate);
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exit(-1);
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}
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int32_t chunk = 0.1 * alsa.GetActualSampleRate();
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std::string last_text;
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auto stream = recognizer.CreateStream();
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sherpa_onnx::Display display;
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int32_t segment_index = 0;
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while (!stop) {
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const std::vector<float> samples = alsa.Read(chunk);
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stream->AcceptWaveform(expected_sample_rate, samples.data(),
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samples.size());
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while (recognizer.IsReady(stream.get())) {
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recognizer.DecodeStream(stream.get());
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}
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auto text = recognizer.GetResult(stream.get()).text;
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bool is_endpoint = recognizer.IsEndpoint(stream.get());
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if (!text.empty() && last_text != text) {
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last_text = text;
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std::transform(text.begin(), text.end(), text.begin(),
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[](auto c) { return std::tolower(c); });
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display.Print(segment_index, text);
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fflush(stderr);
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}
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if (is_endpoint) {
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if (!text.empty()) {
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++segment_index;
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}
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recognizer.Reset(stream.get());
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}
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}
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return 0;
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}
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