Closed leon2milan closed 2 years ago
Hi @leon2milan, We are not planning to train CPC, APC and VQ-VAE based self-supervised speech pre-trained models, instead, we would like to train a WavLM or Data2Vec model on our Mandarin speeches in the future. As for the d-vector or x-vector models, I think they are tasked-specific models trained with labeled data. We aim to release unsupervised speech pre-trained models (upstream models) that researchers could use for their downstream tasks.
@pengchengguo Thank you for your reply.
For wav2vec, I want to test the result of FORCED ALIGNMENT
between WAV2VEC and mfa.
It need load like below:
processor = Wav2Vec2Processor.from_pretrained("facebook/wav2vec2-base-960h")
model = Wav2Vec2ForCTC.from_pretrained("facebook/wav2vec2-base-960h")
I think the last layer of model is (lm_head): Linear(in_features=768, out_features=32, bias=True)
, so I can do forced alignment?
Are facebook's vocab.json
, tokenizer_config.json
files suitable for yours?
If not can you release?
The vocab.json of facebook/wav2vec2 is not suitable for ours. Our model does not have a tokenizer as it was pretrained on audio alone. You can refer to https://huggingface.co/blog/fine-tune-wav2vec2-english to create Wav2Vec2CTCTokenizer and Wav2Vec2Processor for chinese
@LiuShixing Thank you very much.
请问上面的意思是如果需要得到Wav2Vec2CTCTokenizer,需要自己创建词表吗
根据我的理解,Wav2Vec2CTC 模型是在 Wav2Vec2 模型的基础上使用有监督数据,根据 CTC loss,finetune 过的。我们只提供了无监督预训练模型,如果需要 Wav2Vec2CTC 模型,应该要自己进行 finetune。
是的
发自我的iPhone
------------------ Original ------------------ From: cjgdo @.> Date: Mon,Jul 11,2022 3:50 PM To: TencentGameMate/chinese_speech_pretrain @.> Cc: LiuShixing @.>, Mention @.> Subject: Re: [TencentGameMate/chinese_speech_pretrain] New pretrained modelsupport? (Issue #2)
请问上面的意思是如果需要得到Wav2Vec2CTCTokenizer,需要自己创建词表吗
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Will you support new model? like: