ANGIE: A new framework for speech analysis based on morpho-phonological modelling

Abstract

This paper describes a new system for speech analysis, ANGIE, which characterizes word substructure in terms of a trainable grammar. ANGIE capture morpho-phonemic and phonological phenomena through a hierarchical framework. The terminal categories can be alternately letters or phone units, yielding a reversible letter-tosound/sound-to-letter system. In conjunction with a segment network and acoustic phone models, the systemcan produce phonemicto-phonetic alignments for speech waveforms. For speech recognition, ANGIE uses a one-pass bottom-up best-first search strategy. Evaluated in the ATIS domain, ANGIEachieveda phone error rate of 36%, as compared with 40 % achieved with a baseline phone-bigram based recognizer under similar conditions. ANGIEpotentially offers many attractive features, including dynamic vocabulary adaptation, as well as a framework for handling unknown words

Similar works

Full text

thumbnail-image
oai:CiteSeerX.psu:10.1.1.210.6221Last time updated on 10/22/2014

This paper was published in CiteSeerX.

Having an issue?

Is data on this page outdated, violates copyrights or anything else? Report the problem now and we will take corresponding actions after reviewing your request.