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README.md
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path: data/train-*
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- split: test
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path: data/test-*
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---
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path: data/train-*
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- split: test
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path: data/test-*
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task_categories:
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- automatic-speech-recognition
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- text-to-speech
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language:
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- km
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tags:
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- openslr42
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- fleurs
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- asr
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---
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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](): 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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5. resample audio to 16000kHz
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__Disclaimer__ I do not own any of these datasets.
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