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Hi,
To do lexicon-free decoding I set the args.lexicon to False in wsl_decoder.py. But I got an empty string. So Please explain how to do lexicon free decoding. In wsl_decoder.py i have seen this line "lexicon free decoding can only be done with a unit language model" . if that so how can i create unit language model.
Right now I having this below problem in the concurrent lexicon lm model.
For example, In lexicon.txt I have two words tamil and ama. if I send tamil spoken audio to ASR. it predicts as a tamah(no lm). After language model processing it always giving as a ama.
another example:
Now in lexicon.txt I have tamil and am words. If asr predicts as a tamah. the language model giving string as am. I just want to solve this problem. I tried all different value of lm weight or wordgroup parameter but no use. I know that lm_weigt and word group will not influence that much in these scenarios.
Thanks,
Please anyone helpme out. @SenriYoshikawa @mailong25
The text was updated successfully, but these errors were encountered:
Hi,
To do lexicon-free decoding I set the args.lexicon to False in wsl_decoder.py. But I got an empty string. So Please explain how to do lexicon free decoding. In wsl_decoder.py i have seen this line "lexicon free decoding can only be done with a unit language model" . if that so how can i create unit language model.
Right now I having this below problem in the concurrent lexicon lm model.
For example, In lexicon.txt I have two words tamil and ama. if I send tamil spoken audio to ASR. it predicts as a tamah(no lm). After language model processing it always giving as a ama.
another example:
Now in lexicon.txt I have tamil and am words. If asr predicts as a tamah. the language model giving string as am. I just want to solve this problem. I tried all different value of lm weight or wordgroup parameter but no use. I know that lm_weigt and word group will not influence that much in these scenarios.
Thanks,
Please anyone helpme out.
@SenriYoshikawa
@mailong25
The text was updated successfully, but these errors were encountered: