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Wav2Vec2-Conformer

This model was released on 2020-10-11 and added to Hugging Face Transformers on 2022-05-17.

PyTorch

The Wav2Vec2-Conformer was added to an updated version of fairseq S2T: Fast Speech-to-Text Modeling with fairseq by Changhan Wang, Yun Tang, Xutai Ma, Anne Wu, Sravya Popuri, Dmytro Okhonko, Juan Pino.

The official results of the model can be found in Table 3 and Table 4 of the paper.

The Wav2Vec2-Conformer weights were released by the Meta AI team within the Fairseq library.

This model was contributed by patrickvonplaten. The original code can be found here.

Note: Meta (FAIR) released a new version of Wav2Vec2-BERT 2.0 - it’s pretrained on 4.5M hours of audio. We especially recommend using it for fine-tuning tasks, e.g. as per this guide.

  • Wav2Vec2-Conformer follows the same architecture as Wav2Vec2, but replaces the Attention-block with a Conformer-block as introduced in Conformer: Convolution-augmented Transformer for Speech Recognition.
  • For the same number of layers, Wav2Vec2-Conformer requires more parameters than Wav2Vec2, but also yields an improved word error rate.
  • Wav2Vec2-Conformer uses the same tokenizer and feature extractor as Wav2Vec2.
  • Wav2Vec2-Conformer can use either no relative position embeddings, Transformer-XL-like position embeddings, or rotary position embeddings by setting the correct config.position_embeddings_type.

[[autodoc]] Wav2Vec2ConformerConfig

[[autodoc]] models.wav2vec2_conformer.modeling_wav2vec2_conformer.Wav2Vec2ConformerForPreTrainingOutput

[[autodoc]] Wav2Vec2ConformerModel - forward

[[autodoc]] Wav2Vec2ConformerForCTC - forward

Wav2Vec2ConformerForSequenceClassification

Section titled “Wav2Vec2ConformerForSequenceClassification”

[[autodoc]] Wav2Vec2ConformerForSequenceClassification - forward

Wav2Vec2ConformerForAudioFrameClassification

Section titled “Wav2Vec2ConformerForAudioFrameClassification”

[[autodoc]] Wav2Vec2ConformerForAudioFrameClassification - forward

[[autodoc]] Wav2Vec2ConformerForXVector - forward

[[autodoc]] Wav2Vec2ConformerForPreTraining - forward