Comments (2)
freewym
commented on August 15, 2024
You can take WSJ recipe for reference. Like in stage 0&1, you need to use Kaldi for preparing feature/text files (you can use some of the scripts provided in Espresso for doing that). Stage 2 is creating dictionary and tokenizing text into sequences of characters depending on your language (AFAIK Gujarati can follow the same procedure, possibly with minor modifications). The following stages are training LM and E2E models and then decoding.
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freewym
commented on August 15, 2024
I'm going to close it. If you have further questions you can still raise them here.
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Related Issues (20)
- Stream ASR HOT 1
- TypeError: get_asr_dataset_from_json() got an unexpected keyword argument 'combined' HOT 1
- Different WERs when decoding with different batch size (--max-sentences) HOT 5
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- WER difference when decode with different batch size HOT 5
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- SpecAugment is not used due to a typo in the prefetch_called assignment HOT 1
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- How can I find Kaldi directory? HOT 37
- Google Colab research creation HOT 1
- token_text as outputs HOT 2
- Which is the difference between stage 5 and stage 7 HOT 1
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