Speech recognition with a new hybrid architecture combining neural networks and continuous HMM

نویسندگان

  • Daniel Willett
  • Gerhard Rigoll
چکیده

Abstract. In this paper, we focus on a novel NN/HMM architecture for continuous speech recognition. The architecture incorporates a neural feature extraction to gain more discriminative feature vectors for the underlying HMM system. The feature extraction can be chosen either linear or non-linear and can incorporate recurrent connections. With this hybrid system, that is an extension of a state-of-the-art continuous HMM system, we managed to significantly outperform these standard systems. Experimental results show a relative error reduction of about 10% on a remarkably good recognition system based on continuous HMMs for the Resource Management 1000-word continuous speech recognition task.

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

Hybrid HMM/Neural Network based Speech Recognition in Loquendo ASR

This paper describes hybrid Hidden Markov Models / Artificial Neural Networks (HMM/ANN) models devoted to speech recognition, and in particular Loquendo HMM/ANN, that is the core of Loquendo ASR. While Hidden Markov Models (HMM) is a dominant approach in most state-of-the-art speaker-independent, continuous speech recognition systems (and commercial products), Artificial Neural Networks (ANN) a...

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

Hybrid Hmm/ann Systems for Speaker Independent Continuous Speech Recognition in French

| In this paper we report a series of tests carried out on our hybrid HMM/ANN systems which aims at combining Neural Networks theory and Hidden Markov Models (HMMs) for speech recognition of a continuous speech French database: BREF-80. As this database is not manually labelled , we describe a new method based on the temporal alignment of the speech signal on a high quality synthetic speech pat...

متن کامل

— — — — — — — — — A New Approach to Hybrid HMM / ANN Speech

This paper presents a new approach to speech recognition with hybrid HMM/ANN technology. While the standard approach to hybrid HMM/ANN systems is based on the use of neural networks as posterior probability estimators, the new approach is based on the use of mutual information neural networks trained with a special learning algorithm in order to maximize the mutual information between the input...

متن کامل

A New Approach to Hybrid HMM/ANN Speech Recognition using Mutual Information Neural Networks

This paper presents a new approach to speech recognition with hybrid HMM/ANN technology. While the standard approach to hybrid HMMI ANN systems is based on the use of neural networks as posterior probability estimators, the new approach is based on the use of mutual information neural networks trained with a special learning algorithm in order to maximize the mutual information between the inpu...

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 1998