Hybrid neural network/hidden Markov model continuous-speech recognition

نویسندگان

  • Michael Cohen
  • Horacio Franco
  • Nelson Morgan
  • David E. Rumelhart
  • Victor Abrash
چکیده

n M In this paper we present a hybrid multilayer perceptron (MLP)/hidde arkov model (HMM) speaker-independent continuous-speech recognib tion system, in which the advantages of both approaches are combined y using MLPs to estimate the state-dependent observation probabilities p of an HMM. New MLP architectures and training procedures are resented which allow the modeling of multiple distributions for phonetic a p classes and context-dependent phonetic classes. Comparisons with ure HMM system illustrate advantages of the hybrid approach both in terms of recognition accuracy and number of parameters required.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Hybrid Speech Recognition System with Hidden Markov Model and Radial Basis Function Neural Network

We analyze the performance of continuous speech recognition of a speaker independent system using Hidden Markov Model and Artificial Neural Network. Modern speech recognition systems use different combinations of the standard techniques over the basic approach to improve performance accuracy. One such combination which has gained more attention is the hybrid model. Our hybrid system for continu...

متن کامل

Myanmar Language Speech Recognition with Hybrid Artificial Neural Network and Hidden Markov Model

There are many artificial intelligence approaches used in the development of Automatic Speech Recognition (ASR), hybrid approach is one of them. The common hybrid method in speech recognition is the combination of Artificial Neural Network (ANN) and Hidden Markov Model (HMM). The hybrid ANN/HMM is able to classify the phoneme model and to combine the strength of HMM in sequential modeling struc...

متن کامل

Improving Phoneme Sequence Recognition using Phoneme Duration Information in DNN-HSMM

Improving phoneme recognition has attracted the attention of many researchers due to its applications in various fields of speech processing. Recent research achievements show that using deep neural network (DNN) in speech recognition systems significantly improves the performance of these systems. There are two phases in DNN-based phoneme recognition systems including training and testing. Mos...

متن کامل

A Hybrid Stochastic Connectionist Approach to Automatic Speech Recognition

This report focuses on a hybrid approach, including stochastic and connectionist methods , for continuous speech recognition. Hidden Markov Models (HMMs) are a popular stochastic approach used for continuous speech, well suited to cope with the high variability found in natural utterances. On the other hand, artiicial neural networks (NNs) have shown high classiication power for short speech ut...

متن کامل

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 کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1992