Recipes for commonvoice ASR and LID #129
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neillu23
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neillu23
changed the title
Persephone asr
jesus-villalba
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jesus-villalba
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If you haven't, could you pass black on the python files you changed? you can config vscode to do it automatically each time you save, otherwise you can just run "black file_path" on each file.
| t2 = time.time() | ||
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| if output_sampling_rate is not None: | ||
| x = signal.resample(x, int(x.shape[0]*output_sampling_rate/fs)) |
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signal resample may not be a good option, I don't know if it could affect audio quality. I used this function for the VAD because I just wanted to stretch it from frame-level to sample level vad. But I don't know if this function is good for audio. Could you check the audios you got?
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| #!/usr/bin/env python | |||
| """ | |||
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has this faile something different to wav2vec2xvector trainer?
| else: | ||
| assert "duration" in self.seg_set | ||
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run black on this file and other files python file you edited to remove the extra white lines
| parser.add_argument( | ||
| "--base-sampler-type", | ||
| choices=["seg_sampler", "bucketing_seg_sampler"], | ||
| choices=["seg_sampler", "bucketing_seg_sampler", "bucketing_seg_sampler","class_weighted_seg_sampler"], |
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there is a repeated choice
| from .vae.vae import VAE | ||
| from .vae.vq_vae import VQVAE | ||
| from .transducer import RNNTransducer, RNNRNNTransducer | ||
| from .wav2languageid import HFWav2Vec2ResNet1dLanguageID |
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Do we need this one?
| x: torch.Tensor, | ||
| x_lengths: torch.Tensor, | ||
| y: k2.RaggedTensor, | ||
| y: Union[Dict, k2.RaggedTensor], |
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| """ | |||
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can we delete this directory?
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| """ | |||
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I would invert the name to languageid_transducer since we do first the language id and the we want to use it for the asr
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| """ | |||
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can we delete this one?
…erion into persephone-refactor
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