whisper_speech_recognition.cpp

// Copyright (C) 2023-2024 Intel Corporation
// SPDX-License-Identifier: Apache-2.0

#include "audio_utils.hpp"
#include "openvino/genai/whisper_pipeline.hpp"

int main(int argc, char* argv[]) try {
    if (3 > argc) {
        throw std::runtime_error(std::string{"Usage: "} + argv[0] + " <MODEL_DIR> \"<WAV_FILE_PATH>\"");
    }

    std::filesystem::path models_path = argv[1];
    std::string wav_file_path = argv[2];
    std::string device = "CPU";  // GPU, NPU can be used as well

    ov::genai::WhisperPipeline pipeline(models_path, device);

    ov::genai::WhisperGenerationConfig config = pipeline.get_generation_config();
    config.max_new_tokens = 100;  // increase this based on your speech length
    // 'task' and 'language' parameters are supported for multilingual models only
    config.language = "<|en|>";  // can switch to <|zh|> for Chinese language
    config.task = "transcribe";
    config.return_timestamps = true;

    // Pipeline expects normalized audio with Sample Rate of 16kHz
    ov::genai::RawSpeechInput raw_speech = utils::audio::read_wav(wav_file_path);
    auto result = pipeline.generate(raw_speech, config);

    std::cout << result << "\n";

    for (auto& chunk : *result.chunks) {
        std::cout << "timestamps: [" << chunk.start_ts << ", " << chunk.end_ts << "] text: " << chunk.text << "\n";
    }

} catch (const std::exception& error) {
    try {
        std::cerr << error.what() << '\n';
    } catch (const std::ios_base::failure&) {
    }
    return EXIT_FAILURE;
} catch (...) {
    try {
        std::cerr << "Non-exception object thrown\n";
    } catch (const std::ios_base::failure&) {
    }
    return EXIT_FAILURE;
}