facebook
/

wav2vec2-base-960h

Automatic Speech Recognition Transformers PyTorch TensorFlow Safetensors

English wav2vec2 audio hf-asr-leaderboard Eval Results Inference Endpoints

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patrickvonplaten commited on Feb 8, 2021

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1 Parent(s): 3eb23cb

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@@ -62,7 +62,7 @@ To transcribe audio files the model can be used as a standalone acoustic model a
  transcription = tokenizer.batch_decode(predicted_ids)
  ```
- ## Evalution
  This code snippet shows how to evaluate **facebook/wav2vec2-base-960h** on LibriSpeech's "clean" and "other" test data.
@@ -103,4 +103,4 @@ print("WER:", wer(result["text"], result["transcription"]))
 | "clean" | "other" |
 |---|---|
-| 4.1 |   |

  transcription = tokenizer.batch_decode(predicted_ids)
  ```
+ ## Evaluation
  This code snippet shows how to evaluate **facebook/wav2vec2-base-960h** on LibriSpeech's "clean" and "other" test data.
 | "clean" | "other" |
 |---|---|
+| 4.1 | 10.0 |