Large-Vocabulary Speaker-Independent Continuous Speech Recognition with Semi.Continuous Hidden Markov Models
نویسندگان
چکیده
A semi-continuous hidden Markov model based on the muluple vector quantization codebooks is used here for large.vocabulary speaker-independent continuous speech recognition in the techn,ques employed here. the semi-continuous output probab~hty densHy function for each codebook is represented by a comhinat,on of the corre,~ponding discrete output probablhttes of the hidden Markov model end the continuous Gauss,an den. stay functions of each individual codebook. Parameters of vec. tor qusnttzation codebook and hidden Markov model are mutuully optimized to achJeve an optimal model'codebook comb,nation under a untried probab,hshc framework Another advantages of thts approach is the enhanced robustness of the semi. continuous output probability by the combination of multiple codewords and multtple codebooks For a 1000.word speakermdependent continuous speech recognition using a word.pa,r grammar, the recogmtion error rate of the semi-conhnuouq bud. den Markov model was reduced by more than 29'~ and 41"3 in comparison to the discrete and continuous mixture htdden Mar. kay model respectively
منابع مشابه
Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words
متن کامل
Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words
متن کامل
Large Vocabulary Continuous Speech Recognition
Large vocabulary speaker-independent speech recognition systems being capable of recognizing continuous speech based on hidden Markov models are today’s standard. This review introduces the fundamentals of speech and the underlying speech recognition problems. The three classical approaches, i.e., the acoustic-phonetic, the statistical (pattern) recognition and the artificial intelligence appro...
متن کاملMultiple codebook semi-continuous hidden Markov models for speaker-independent continuous speech recognition
A semi-continuous hidden Markov model based on the multiple vector quantization codebooks is used here for large-vocabulary speaker-independent continuous speech recognition. In the techniques employed here, the semi-continuous output probability density function for each codebook is represented by a combination of the corresponding discrete output probabilities of the hidden Markov model and t...
متن کاملLimited-Vocabulary Estonian Continuous Speech Recognition System using Hidden Markov Models
The article presents a limited-vocabulary speaker independent continuous Estonian speech recognition system based on hidden Markov models. The system is trained using an annotated Estonian speech database of 60 speakers, approximately 4 hours in duration. Words are modelled using clustered triphones with multiple Gaussian mixture components. The system is evaluated using a number recognition ta...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1989