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@@ -14,6 +14,31 @@ widget:
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  src: https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h/raw/main/audio-test/t1_utt000000042.wav
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  - label: VLSP ASR 2020 test T2
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  src: https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h/raw/main/audio-test/t2_0000006682.wav
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Wav2Vec2-Base-250h for the Vietnamese language
@@ -40,10 +65,10 @@ Detail of training and fine-tuning process, the audience can follow [fairseq git
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  ### Benchmark WER result:
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- | | [VIVOS](https://ailab.hcmus.edu.vn/vivos) | [VLSP-T1](https://vlsp.org.vn/vlsp2020/eval/asr) | [VLSP-T2](https://vlsp.org.vn/vlsp2020/eval/asr) |
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- |---|---|---|---|
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- |without LM| 10.77 | 13.33 | 51.45 |
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- |with 4-grams LM| 6.15 | 9.11 | 40.81 |
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  ### Example usage
 
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  src: https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h/raw/main/audio-test/t1_utt000000042.wav
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  - label: VLSP ASR 2020 test T2
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  src: https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h/raw/main/audio-test/t2_0000006682.wav
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+ model-index:
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+ - name: Vietnamese end-to-end speech recognition using wav2vec 2.0 by VietAI
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+ results:
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+ - task:
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+ name: Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: Common Voice vi
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+ type: common_voice
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+ args: vi
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+ metrics:
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+ - name: Test WER
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+ type: wer
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+ value: 11.52
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+ - task:
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+ name: Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: VIVOS
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+ type: vivos
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+ args: vi
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+ metrics:
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+ - name: Test WER
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+ type: wer
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+ value: 6.15
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  ---
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  # Wav2Vec2-Base-250h for the Vietnamese language
 
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  ### Benchmark WER result:
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+ | | [VIVOS](https://ailab.hcmus.edu.vn/vivos) | [COMMON VOICE VI](https://paperswithcode.com/dataset/common-voice) | [VLSP-T1](https://vlsp.org.vn/vlsp2020/eval/asr) | [VLSP-T2](https://vlsp.org.vn/vlsp2020/eval/asr) |
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+ |---|---|---|---|---|
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+ |without LM| 10.77 | 18.34 | 13.33 | 51.45 |
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+ |with 4-grams LM| 6.15 | 11.52 | 9.11 | 40.81 |
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  ### Example usage