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README.md
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- thennal/IMaSC
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language:
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- ml
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---
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WER - 24.83
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CER - 12.84
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In SMC dataset
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WER - 27.28
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CER - 14.64
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- thennal/IMaSC
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language:
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- ml
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model-index:
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- name: Malwhisper-v1-small - Kurian Benoy
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results:
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- task:
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type: automatic-speech-recognition
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name: Automatic Speech Recognition
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dataset:
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name: Common Voice 11.0
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type: mozilla-foundation/common_voice_11_0
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config: ml
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split: test
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args: ml
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metrics:
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- type: wer
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value: 24.83
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name: WER
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library_name: transformers
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---
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## kurianbenoy/Malwhisper-v1-small
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) fine-tuned on [IMASc dataset](https://www.kaggle.com/datasets/thennal/imasc).
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IMaSC is a Malayalam text and speech corpus made available by ICFOSS for the purpose of developing speech technology for Malayalam, particularly text-to-speech. The corpus contains 34,473 text-audio pairs of Malayalam sentences spoken by 8 speakers, totalling in approximately 50 hours of audio.
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The fine-tuned model on evaluating in the following dataset:
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**In Mozilla CommonVoice 11.0 dataset (Malayalam subset):**
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WER - 24.83
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CER - 12.84
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**In SMC Malayalam Speech Corpus dataset:**
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WER - 27.28
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CER - 14.64
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