--- language: en datasets: - common_voice - mozilla-foundation/common_voice_6_0 metrics: - wer - cer tags: - audio - automatic-speech-recognition - en - hf-asr-leaderboard - mozilla-foundation/common_voice_6_0 - robust-speech-event - speech - xlsr-fine-tuning-week license: apache-2.0 model-index: - name: XLSR Wav2Vec2 English results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice en type: common_voice args: en metrics: - name: Test WER type: wer value: 19.06 - name: Test CER type: cer value: 7.69 - name: Test WER (+LM) type: wer value: 14.81 - name: Test CER (+LM) type: cer value: 6.84 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Robust Speech Event - Dev Data type: speech-recognition-community-v2/dev_data args: en metrics: - name: Dev WER type: wer value: 27.72 - name: Dev CER type: cer value: 11.65 - name: Dev WER (+LM) type: wer value: 20.85 - name: Dev CER (+LM) type: cer value: 11.01 library_name: transformers --- # Fine-tuned XLSR-53 large model for speech recognition in English Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on English using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice). When using this model, make sure that your speech input is sampled at 16kHz.