Among speaker adaptation algorithms, eigenvoice (EV) and eigenspace-based MLLR (EMLLR) adaptation approaches have been proposed for rapid adaptation with very limited adaptation data. In these methods, a speaker adapted model is constrained to be a weighted combination of some orthogonal basis vectors. In this manner, both the number of parameters to be estimated from the adaptation data, and t...

With the demand on providing automatic speech recognition (ASR) systems for many markets the question of porting an ASR system to a new language is of practical interest. To cope with this task the adaptation of hidden Markov models (HMM) is seen as a key step to transfer the models from a source to a target language. In this work we introduce a novel adaptation scheme for semi-continuous HMMs ...

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...

Based on Bell Labs speech recognition and understanding technology, we developed LASR3 (Lucent Automatic Speech Recognition, Version 3), a speaker independent, software-based continuous speech recognition engine. It is compatible with Microsoft Speech Application Programming Interface (MS SAPI)[1]. LASR3 provides support for desktop, telephony, and internet applications requiring speech recogni...

This paper investigates the effectiveness of the DAEM (Deterministic Annealing EM) algorithm in acoustic modeling for speaker and speech recognition. Although the EM algorithm has been widely used to approximate the ML estimates, it has the problem of initialization dependence. To relax this problem, the DAEM algorithm has been proposed and confirmed the effectiveness in small tasks. In this pa...

The Lister Hill National Center for Biomedical Communications, an R&D division of the National Library of Medicine, has developed a PC-based system for semi-automated entry of journal citation data into MEDLINE®. The system, called MARS for Medical Article Records System, includes many automated features but requires a few manual tasks such as scanning and the entry of certain data that are not...

In this article, we have introduced the first parallel corpus of Persian with more than 10 other European languages. This article describes primary steps toward preparing a Basic Language Resources Kit (BLARK) for Persian. Up to now, we have proposed morphosyntactic specification of Persian based on EAGLE/MULTEXT guidelines and specific resources of MULTEXT-East. The article introduces Persian ...

We study the problem of phonetic modeling for continuous Mandarin speech recognition by providing a systematic performance comparison for systems based on following primitive speech units: syllable, demi-syllable (Initials and Finals), context-independent phones, left-or-right context-dependentphones (diphones), and leftand-right context-dependent phones (triphones). In our speakerdependent con...

This paper presents the statistical part-ofspeech tagger HunPoS trained on a Persian corpus. The result of the experiments shows that HunPoS provides an overall accuracy of 96.9%, which is the best result reported for Persian part-of-speech tagging.

This paper describes the continuous speech recognition subsystem "ATREUS" which is used as the speech input stage in the experimental speech translation system "ASURA." The speech recognition algorithm is SSS-LR/VFS which consists of context-dependent phone models (HMnet), a generalized LR parser, and vector field smoothing for speaker / environment adaptation. (1993): "ATREUS: a speech recogni...