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  - asr
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  ---
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- This dataset combined [google/fleurs](https://huggingface.co/datasets/google/fleurs){:target="_blank"} , [openslr/openslr42](https://huggingface.co/datasets/openslr/openslr){:target="_blank"}, and cleaned [seanghay/khmer_mpwt_speech](https://huggingface.co/datasets/seanghay/khmer_mpwt_speech){:target="_blank"}.
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  Severals processes are executed:
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- 1. clean up [seanghay/khmer_mpwt_speech](): manually correct wrong transcriptions over 2058 rows
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  2. normalize transcription: remove invisible white space; process `ៗ`, numbers, currencies, date into khmer text; and separate each word by space
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  3. filter out texts whose number of token ids are more than 448: use tokenizer of Whisper-Small to encode text and filter out sequences longer than 448
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  4. filter out audio with length longer than 30 seconds
 
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  - asr
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+ This dataset combined [google/fleurs](https://huggingface.co/datasets/google/fleurs), [openslr/openslr42](https://huggingface.co/datasets/openslr/openslr), and cleaned [seanghay/khmer_mpwt_speech](https://huggingface.co/datasets/seanghay/khmer_mpwt_speech).
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  Severals processes are executed:
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+ 1. clean up [seanghay/khmer_mpwt_speech](https://huggingface.co/datasets/seanghay/khmer_mpwt_speech): manually correct wrong transcriptions over 2058 rows
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  2. normalize transcription: remove invisible white space; process `ៗ`, numbers, currencies, date into khmer text; and separate each word by space
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  3. filter out texts whose number of token ids are more than 448: use tokenizer of Whisper-Small to encode text and filter out sequences longer than 448
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  4. filter out audio with length longer than 30 seconds