Wav2Vec2 Conformer Large 960h with Rotary Position Embeddings Wav2Vec2 Conformer with rotary position embeddings, pretrained and fine tuned on 960 hours of Librispeech on 16kHz sampled speech audio. When using the model make sure that your speech input is also sampled at 16Khz. Paper : fairseq S2T: Fast Speech to Text Modeling with fairseq Authors : Changhan Wang, Yun Tang, Xutai Ma, Anne Wu, Sravya Popuri, Dmytro Okhonko, Juan Pino The results of Wav2Vec2 Conformer can be found in Table 3 and Table 4 of the official paper. The original model can be found under https://github.com/pytorch/fairseq/tree/master/examples/wav2vec wav2vec 20. Usage To transcribe audio files the model can be used as a standalone acoustic model as follows: Evaluation This code snippet shows how to evaluate facebook/wav2vec2 conformer rope large 960h ft on LibriSpeech's "clean" and "other" test data. Result (WER) : "clean" "other" 1.96 3.98
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