Automatically assigned DDC number:

Manually assigned DDC number: 006454

Number of references: 4

Title: Hierarchical Duration Modelling for a Speech Recognition System

Author:

Author:

Subject: Grace Chung,Stephanie Seneff Hierarchical Duration Modelling for a Speech Recognition System

Description: Durational patterns of phonetic segments and pauses convey information about the linguistic content of an utterance. Most speech recognition systems grossly underutilize the knowledge provided by durational cues due to the vast array of factors that influence speech timing and the complexity with which they interact. In this thesis, we introduce a duration model based on the Angie framework. Angie is a paradigm which captures morpho-phonemic and phonological phenomena under a unified hierarchical structure. Sublexical parse trees provided by Angie are well-suited for constructing complex statistical models to account for durational patterns that are functions of effects at various linguistic levels. By constructing models for all the sublexical nodes of a parse tree, we implicitly model duration phenomena at these linguistic levels simultaneously, and subsequently account for a vast array of contextual variables affecting duration from the phone level up to the word level. This thesis...

Contributor: The Pennsylvania State University CiteSeer Archives

Publisher: unknown

Date: 1997-10-10

Pubyear: 1997

Format: ps

Identifier: http://citeseer.ist.psu.edu/142071.html

Source: http://www.sls.lcs.mit.edu/sls/publications/1997/smthesis-graceyc.ps.gz

Language: en

Relation:

Relation:

Relation:

Relation:

Rights: unrestricted

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