| import librosa |
| from model_clap import CLAPEmbedding |
| from model_meta_voice import MetaVoiceEmbedding |
| from model_pyannote_embedding import PyannoteEmbedding |
| from model_speaker_embedding import W2VBERTEmbedding, XLSR300MEmbedding, HuBERTXLEmbedding |
|
|
|
|
| def test(): |
| wav, sr = librosa.load("sample.wav") |
| print("XLS-R") |
| model = XLSR300MEmbedding() |
| v = model.get_speaker_embedding(wav, sr) |
| print(v.shape) |
| print("CLAP") |
| model = CLAPEmbedding() |
| v = model.get_speaker_embedding(wav, sr) |
| print(v.shape) |
| print("MetaVoiceSE") |
| model = MetaVoiceEmbedding() |
| v = model.get_speaker_embedding(wav, sr) |
| print(v.shape) |
| print("PyannoteSE") |
| model = PyannoteEmbedding() |
| v = model.get_speaker_embedding(wav, sr) |
| print(v.shape) |
| print("W2VBertSE") |
| model = W2VBERTEmbedding() |
| v = model.get_speaker_embedding(wav, sr) |
| print(v.shape) |
| print("huBERT") |
| model = HuBERTXLEmbedding() |
| v = model.get_speaker_embedding(wav, sr) |
| print(v.shape) |
|
|
|
|
| if __name__ == '__main__': |
| test() |
|
|