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enginex-mr_series-sherpa-onnx/sherpa-onnx/csrc/sherpa-onnx-keyword-spotter.cc
2024-04-24 18:41:48 +08:00

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3.2 KiB
C++

// sherpa-onnx/csrc/sherpa-onnx-keyword-spotter.cc
//
// Copyright (c) 2023-2024 Xiaomi Corporation
#include <stdio.h>
#include <iomanip>
#include <iostream>
#include <string>
#include <vector>
#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<sherpa_onnx::OnlineStream> 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<Stream> 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<float> 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<float> tail_paddings(static_cast<int>(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<sherpa_onnx::OnlineStream *> 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;
}