ASR - Articulatory Speech Recognition

J. Frankel; S. King

ASR - Articulatory Speech Recognition

J. Frankel, S. King

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper we report recent work on a speech recognition system using a combination of acoustic and articulatory features as input. Linear dynamic models are used to capture the trajectories which characterize each segment type. We describe classification and recognition tasks for systems based on acoustic data in conjunction with both real and automatically recovered articulatory parameters.

Original language	English
Title of host publication	Eurospeech 2001
Subtitle of host publication	7th European Conference on Speech Communication and Technology
Publisher	International Speech Communication Association
Pages	599-602
Number of pages	4
ISBN (Print)	ISSN: 1990-9772
Publication status	Published - 1 Sep 2001

ROPA: SPEECH RECOGNITION
King, S.
EPSRC
1/10/99 → 31/01/02
Project: Research

Cite this

@inproceedings{644a8fe47bc8402aa84e3d850156923c,

title = "ASR - Articulatory Speech Recognition",

abstract = "In this paper we report recent work on a speech recognition system using a combination of acoustic and articulatory features as input. Linear dynamic models are used to capture the trajectories which characterize each segment type. We describe classification and recognition tasks for systems based on acoustic data in conjunction with both real and automatically recovered articulatory parameters.",

author = "J. Frankel and S. King",

note = "ISSN: 1990-9772",

year = "2001",

month = sep,

day = "1",

language = "English",

isbn = "ISSN: 1990-9772",

pages = "599--602",

booktitle = "Eurospeech 2001",

publisher = "International Speech Communication Association",

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TY - GEN

T1 - ASR - Articulatory Speech Recognition

AU - Frankel, J.

AU - King, S.

N1 - ISSN: 1990-9772

PY - 2001/9/1

Y1 - 2001/9/1

N2 - In this paper we report recent work on a speech recognition system using a combination of acoustic and articulatory features as input. Linear dynamic models are used to capture the trajectories which characterize each segment type. We describe classification and recognition tasks for systems based on acoustic data in conjunction with both real and automatically recovered articulatory parameters.

AB - In this paper we report recent work on a speech recognition system using a combination of acoustic and articulatory features as input. Linear dynamic models are used to capture the trajectories which characterize each segment type. We describe classification and recognition tasks for systems based on acoustic data in conjunction with both real and automatically recovered articulatory parameters.

M3 - Conference contribution

SN - ISSN: 1990-9772

SP - 599

EP - 602

BT - Eurospeech 2001

PB - International Speech Communication Association

ER -

ASR - Articulatory Speech Recognition

Abstract

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Projects

ROPA: SPEECH RECOGNITION

Cite this