df4615ca1d
This PR introduces support for NeMo Canary models across C, C++, and JavaScript APIs by adding new Canary configuration structures, updating bindings, extending examples, and enhancing CI workflows. - Add OfflineCanaryModelConfig to all language bindings (C, C++, JS, ETS). - Implement SetConfig methods and NAPI wrappers for updating recognizer config at runtime. - Update examples and CI scripts to demonstrate and test NeMo Canary model usage.
102 lines
3.2 KiB
C++
102 lines
3.2 KiB
C++
// cxx-api-examples/nemo-canary-cxx-api.cc
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//
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// Copyright (c) 2025 Xiaomi Corporation
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//
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// This file demonstrates how to use NeMo Canary models with
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// sherpa-onnx's C++ API.
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//
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// clang-format off
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//
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// wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8.tar.bz2
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// tar xvf sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8.tar.bz2
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// rm sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8.tar.bz2
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//
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// clang-format on
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//
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// see https://k2-fsa.github.io/sherpa/onnx/nemo/canary.html
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// for details
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#include <chrono> // NOLINT
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#include <iostream>
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#include <string>
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#include "sherpa-onnx/c-api/cxx-api.h"
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int32_t main() {
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using namespace sherpa_onnx::cxx; // NOLINT
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OfflineRecognizerConfig config;
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config.model_config.canary.encoder =
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"sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/encoder.int8.onnx";
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config.model_config.canary.decoder =
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"sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/decoder.int8.onnx";
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// our input audio is German, so we set src_lang to "de"
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config.model_config.canary.src_lang = "de";
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// we can set tgt_lang either to de or en in this specific case
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config.model_config.canary.tgt_lang = "en";
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config.model_config.tokens =
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"sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/tokens.txt";
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config.model_config.num_threads = 1;
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std::cout << "Loading model\n";
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OfflineRecognizer recognizer = OfflineRecognizer::Create(config);
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if (!recognizer.Get()) {
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std::cerr << "Please check your config\n";
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return -1;
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}
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std::cout << "Loading model done\n";
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std::string wave_filename =
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"./sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8/test_wavs/de.wav";
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Wave wave = ReadWave(wave_filename);
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if (wave.samples.empty()) {
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std::cerr << "Failed to read: '" << wave_filename << "'\n";
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return -1;
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}
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std::cout << "Start recognition\n";
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const auto begin = std::chrono::steady_clock::now();
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OfflineStream stream = recognizer.CreateStream();
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stream.AcceptWaveform(wave.sample_rate, wave.samples.data(),
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wave.samples.size());
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recognizer.Decode(&stream);
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OfflineRecognizerResult result = recognizer.GetResult(&stream);
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const auto end = std::chrono::steady_clock::now();
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const 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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float duration = wave.samples.size() / static_cast<float>(wave.sample_rate);
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float rtf = elapsed_seconds / duration;
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std::cout << "text (English): " << result.text << "\n";
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printf("Number of threads: %d\n", config.model_config.num_threads);
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printf("Duration: %.3fs\n", duration);
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printf("Elapsed seconds: %.3fs\n", elapsed_seconds);
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printf("(Real time factor) RTF = %.3f / %.3f = %.3f\n", elapsed_seconds,
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duration, rtf);
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// now output text in German
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config.model_config.canary.tgt_lang = "de";
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recognizer.SetConfig(config);
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stream = recognizer.CreateStream();
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stream.AcceptWaveform(wave.sample_rate, wave.samples.data(),
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wave.samples.size());
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recognizer.Decode(&stream);
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result = recognizer.GetResult(&stream);
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std::cout << "text (German): " << result.text << "\n";
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return 0;
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}
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