Fast algorithm for speech recognition using speaker cluster HMM
نویسندگان
چکیده
This paper describes a high speed algorithm for a speech recognizer based on speaker cluster HMM. The speaker cluster HMM, which enables to deal with variety among speakers, have been reported to show good performance. However, the computation amount grows in proportion to the number of clusters, when the speaker cluster HMM is used in speaker independent recognition, where the recognition processes must be run in parallel using every speaker cluster HMM. To reduce the computation, we introduced the multi-pass search for searching on the broad space covering lexical and speaker variation. Furthermore, the output probability recalculation is introduced to reduce the state output probability computation. We had some experiments on 1000 word speaker independent continuous telephone speech recognition. The result in the case where 7 speaker clusters are used shows about 30% of computation reduction.
منابع مشابه
شبکه عصبی پیچشی با پنجرههای قابل تطبیق برای بازشناسی گفتار
Although, speech recognition systems are widely used and their accuracies are continuously increased, there is a considerable performance gap between their accuracies and human recognition ability. This is partially due to high speaker variations in speech signal. Deep neural networks are among the best tools for acoustic modeling. Recently, using hybrid deep neural network and hidden Markov mo...
متن کاملSpeaker Dependent and Independent Isolated Hindi Word Recognizer using Hidden Markov Model (HMM)
Hindi is very complex language with large number of phonemes and being used with various ascents in different regions in India. In this manuscript, speaker dependent and independent isolated Hindi word recognizers using the Hidden Markov Model (HMM) is implemented, under noisy environment. For this study, a set of 10 Hindi names has been chosen as a test set for which the training and testing i...
متن کاملAutomatic Continuous Speech Recognition with Rapid Speaker Adaptation for Human/machine Interaction
This thesis presents work in three main directions of the automatic speech recognition field. The work within two of these – dynamic decoding and hybrid HMM/ANN speech recognition – has resulted in a real-time speech recognition system, currently in use in the human/machine dialogue demonstration system WAXHOLM, developed at the department. The third direction is fast unsupervised speaker adapt...
متن کاملMandarin telephone speech recognition using MCE/GPD-based speaker cluster HMM
In this paper we successfully apply the MCE/GPD method to train speaker cluster HMM. The essential concept of our approach is to adjust all the parameters of the speaker cluster HMM simultaneously using each utterance of the whole training set. In other words, the parameters of each cluster-dependent HMM are no longer independently estimated by using only the training data of the speakers who b...
متن کاملEnglish Sentence Recognition Based on HMM and Clustering
For English sentences with a large amount of feature data and complex pronunciation changes contrast to words, there are more problems existing in Hidden Markov Model (HMM), such as the computational complexity of the Viterbi algorithm and mixed Gaussian distribution probability. This article explores the segment-mean algorithm for dimensionality reduction of speech feature parameters, the clus...
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 1997