Acoustical analysis of speech is considered a favorable and promising approach to objective assessment of voice disorders. Previous research emphasized on the extraction and classification of voice quality features from sustained vowel sounds. In this paper, an investigation on voice assessment using continuous speech utterances of Cantonese is presented. A DNN-HMM based speech recognition syst...

How do people conceptualize motion events and talk about them? The current study examines how gestural representations of motion events arise from linguistic expressions in Persian, which has characteristics of both Talmy’s satelliteand verb-framed languages. We examined native Persian speakers’ speech and gestures in describing 20 motion events. We focused on two motion event components: path ...

OBJECTIVE Our objective was to describe our experience with a commercially available continuous speech recognition system, highlighting the advantages, disadvantages, and costs compared with those of conventional transcription for MR imaging reports. MATERIALS AND METHODS Data from 5072 reports generated in our MR imaging section during a 9-month period after the implementation of a commercia...

A variety of methods are used for speaker adaptation in speech recognition. In some techniques, such as MAP estimation, only the models with available training data are updated. Hence, large amounts of training data are required in order to have significant recognition improvements. In some others, such as MLLR, where several general transformations are applied to model clusters, the results ar...

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...

In October 2002, European Telecommunications Standards Institute (ETSI) recommended a standard Distributed Speech Recognition (DSR) advanced front-end, ETSI ES202 050 version 1.1.1 (ES202). Many studies use this front-end in noise environments on several languages on connected digit recognition tasks. However, we have not seen the reports of large vocabulary continuous speech recognition using ...

Pronunciation variations are common sources of recognition errors in real-world applications, so that specific techniques must be developed to handle them. We are describing a method to incorporate pronunciation alternatives that have been tested with both continuous and isolated word speech recognisers for Spanish. We present an automatic grapheme-tophoneme system, modified to generate alterna...

In spite of the recent advancements being made in speech recognition, recognition errors are unavoidable in continuous speech recognition. In this paper, we focus on a word-error correction system for continuous speech recognition using confusion networks. Conventional N -gram correction is widely used; however, the performance degrades due to the fact that the N -gram approach cannot measure i...

This paper presents the rst published results for automatic recognition of continuous Cantonese speech with very large vocabulary. The size of the vocabulary covered by this system is about the same as that encountered in the Hong Kong local Chinese newspaper, Wen Hui Bao (å×ø ). The system covers 6335 Chinese characters (r) and a large number of Chinese words (ü) can be formed by combining the...

In this paper, a new acoustic model called time-inhomogeneous hidden Bernoulli model (TI-HBM) is introduced as an alternative to hidden Markov model (HMM) in continuous speech recognition. Contrary to HMM, the state transition process in TI-HBM is not a Markov process, rather it is an independent (generalized Bernoulli) process. This difference leads to elimination of dynamic programming at sta...