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import os |
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import torch |
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from openvoice import se_extractor |
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from openvoice.api import ToneColorConverter |
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ckpt_converter = 'checkpoints_v2/converter' |
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device = "cuda:0" if torch.cuda.is_available() else "cpu" |
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output_dir = 'outputs_v2' |
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tone_color_converter = ToneColorConverter(f'{ckpt_converter}/config.json', device=device) |
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tone_color_converter.load_ckpt(f'{ckpt_converter}/checkpoint.pth') |
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os.makedirs(output_dir, exist_ok=True) |
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reference_speaker = 'resources/example_reference.mp3' |
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target_se, audio_name = se_extractor.get_se(reference_speaker, tone_color_converter, vad=True) |
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from melo.api import TTS |
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texts = { |
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'EN_NEWEST': "Did you ever hear a folk tale about a giant turtle?", |
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'EN': "Did you ever hear a folk tale about a giant turtle?", |
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'ES': "El resplandor del sol acaricia las olas, pintando el cielo con una paleta deslumbrante.", |
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'FR': "La lueur dorée du soleil caresse les vagues, peignant le ciel d'une palette éblouissante.", |
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'ZH': "在这次vacation中,我们计划去Paris欣赏埃菲尔铁塔和卢浮宫的美景。", |
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'JP': "彼は毎朝ジョギングをして体を健康に保っています。", |
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'KR': "안녕하세요! 오늘은 날씨가 정말 좋네요.", |
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} |
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src_path = f'{output_dir}/tmp.wav' |
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speed = 1.0 |
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for language, text in texts.items(): |
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model = TTS(language=language, device=device) |
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speaker_ids = model.hps.data.spk2id |
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for speaker_key in speaker_ids.keys(): |
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speaker_id = speaker_ids[speaker_key] |
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speaker_key = speaker_key.lower().replace('_', '-') |
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source_se = torch.load(f'checkpoints_v2/base_speakers/ses/{speaker_key}.pth', map_location=device) |
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if torch.backends.mps.is_available() and device == 'cpu': |
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torch.backends.mps.is_available = lambda: False |
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model.tts_to_file(text, speaker_id, src_path, speed=speed) |
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save_path = f'{output_dir}/output_v2_{speaker_key}.wav' |
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encode_message = "@MyShell" |
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tone_color_converter.convert( |
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audio_src_path=src_path, |
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src_se=source_se, |
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tgt_se=target_se, |
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output_path=save_path, |
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message=encode_message) |
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print("done.") |
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