Study of Hidden Markov Models and Neural Networks for Robust Isolated Word Recognition

Objective

The dominant technology is Hidden Markov Models (HMMs) but this has significant limitations, some of which could be alleviated by the judicious use of artificial neural networks (ANNs) or hybrid combinations of both techniques.

Direct comparisons of ANN-based, HMM-based, and hybrid ANN/HMM techniques for speech recognition will be made. The developments will be integrated and validated in the context of a telephone application including speech recognition capabilities.

A number of prototypes have been demonstrated on low cost commodity systems.

The telephone application developed within the project will be the basis for product development by Tedas.

Fields of science

• natural sciences › computer and information sciences › artificial intelligence › computational intelligence

Programme(s)

• FP3-ESPRIT 3 - Specific research and technological development programme (EEC) in the field of information technologies, 1990-1994

Topic(s)

Data not available

Call for proposal

Data not available

Funding Scheme

Data not available

Coordinator

FACULTÉ POLYTECHNIQUE DE MONS

Address

Boulevard Dolez, 31
7000 Mons
Belgium

Participants (4)

ASCOM TECH AG

Switzerland

Address

Belpstrasse, 23
3000 Bern

ECOLE POLYTECHNIQUE DE LAUSANNE

Switzerland

Address

Avenue De Cour, 37
1007 Lausanne

LEERNHOUT & HAUSPIE SPEECHPRODUCTS

Belgium

Address

Rozendaalstraat, 14
8900 Ieper

TEDAS GESELLSCHAFT FÜR TECHNISCHE DATENVERARBEITUNG MBH

Germany

Address

Universitätsstraße 51
35037 Marburg