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@@ -8,9 +8,8 @@ This repository contains evaluation results from the Malayalam ASR model "vrclc/
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  ### Evaluation Results
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  * Dataset Description: The test set of [google/fleurs](https://huggingface.co/datasets/google/fleurs/viewer/ml_in/test) dataset which consists of Malayalam speech data.
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  * Model Training: [vrclc/Whisper_small_malayalam](https://huggingface.co/vrclc/Whisper_small_malayalam) was trained with 50 hours of Malayalam speech data.
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- * Evaluation Metric:
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- 1. The unnormalized evaluation result of 500 samples from [google/fleurs](https://huggingface.co/datasets/google/fleurs/viewer/ml_in/test) and the WER is 60.4%.
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- 2. Punctuation normalized evaluation result of same test set and the WER is 52%
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  This repository serves to provide an insight in error analysis which helps to identify general mistakes and areas for improvement in Malayalam speech recognition.
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  ### Evaluation Results
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  * Dataset Description: The test set of [google/fleurs](https://huggingface.co/datasets/google/fleurs/viewer/ml_in/test) dataset which consists of Malayalam speech data.
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  * Model Training: [vrclc/Whisper_small_malayalam](https://huggingface.co/vrclc/Whisper_small_malayalam) was trained with 50 hours of Malayalam speech data.
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+ * Evaluation Metric:The unnormalized evaluation result of 500 samples from [google/fleurs](https://huggingface.co/datasets/google/fleurs/viewer/ml_in/test) and the WER is 60.4%.
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  This repository serves to provide an insight in error analysis which helps to identify general mistakes and areas for improvement in Malayalam speech recognition.
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