I'm currently working on a speech recognition project. This project require to recognize just single word instead of whole sentence. Currently the WER is just too high. How do I programatically reduce the WER? Can I check the tokens and scores and filter out result with low scores or too many tokens?
Thanks.
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A lot of this depends upon your task. If you have a relatively small vocabulary where the user might say any of the words with equal probability, you might consider using a trivial JSGF grammar that is a simple word list. If you have some idea of the probabilities of the words, you could also try adding weights to the words.
To tune the engine, there are a number of parameters you can set. For JSGF grammars, you might try setting the following parameters in the linguist:
The bunch of these together should tell calls to getBestResultNoFiller to return "<unk>" if Sphinx-4 thinks the utterance is out of grammar. You can read more about this in the FAQ:
Hi,
I'm currently working on a speech recognition project. This project require to recognize just single word instead of whole sentence. Currently the WER is just too high. How do I programatically reduce the WER? Can I check the tokens and scores and filter out result with low scores or too many tokens?
Thanks.
Hi Weiheng:
A lot of this depends upon your task. If you have a relatively small vocabulary where the user might say any of the words with equal probability, you might consider using a trivial JSGF grammar that is a simple word list. If you have some idea of the probabilities of the words, you could also try adding weights to the words.
To tune the engine, there are a number of parameters you can set. For JSGF grammars, you might try setting the following parameters in the linguist:
The bunch of these together should tell calls to getBestResultNoFiller to return "<unk>" if Sphinx-4 thinks the utterance is out of grammar. You can read more about this in the FAQ:
http://cmusphinx.sourceforge.net/sphinx4/doc/Sphinx4-faq.html#out_of_grammar
Note, however, that if you have individual words that can be easily confused (e.g., "on"/"off" "cat"/"fat"), you may still end up with poor results.
Hope this helps,
Will
PS - You might also take a look at the demo/sphinx/confidence/ demo.