Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: HTK is a portable software toolkit for building speech recognition systems using continuous density hidden Markov models developed by the Cambridge University Speech Group. One particularly successful type of system uses mixture density tied-state triphones.  have used this technique for the 5 k/20 k word ARPA Wall Street Journal (WSJ) task.  have extended our approach from using word-internal gender independent modelling to use decision tree based state clustering, cross-word triphones and gender dependent models. Our current systems can be run with either bigram or trigram language models using a single pass dynamic network decoder. Systems based on these techniques re included in the November 1993 ARPA WSJ evaluation, and gave the lost error rate reported on the 5 k word bigram, 5 k word trigram and 20 k word bigram "hub" tests and the second lost error rate on the 20 k word trigram "hub" test. >
['Philip C. Woodland', 'Julian J. Odell', 'Valtcho Valtchev', 'Steve J. Young']
I am writing a research paper on a idea Large vocabulary continuous speech recognition using HTK
[{"from": "human", "value": "I am writing a research paper on a idea Large vocabulary continuous speech recognition using HTK"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: HTK is a portable software toolkit for building speech recognition systems using continuous density hidden Markov models developed by the Cambridge University Speech Group. One particularly successful type of system uses mixture density tied-state triphones.  have used this technique for the 5 k/20 k word ARPA Wall Street Journal (WSJ) task.  have extended our approach from using word-internal gender independent modelling to use decision tree based state clustering, cross-word triphones and gender dependent models. Our current systems can be run with either bigram or trigram language models using a single pass dynamic network decoder. Systems based on these techniques re included in the November 1993 ARPA WSJ evaluation, and gave the lost error rate reported on the 5 k word bigram, 5 k word trigram and 20 k word bigram \"hub\" tests and the second lost error rate on the 20 k word trigram \"hub\" test. >"}]