Title :
Using neural networks for a discriminant speech recognition system
Author :
ŞChiopu, Daniela ; Oprea, Mihaela
Author_Institution :
Pet.-Gas Univ. of Ploiesti, Ploieşti, Romania
Abstract :
The paper presents a case study of using neural networks for a discriminant automatic speech recognition system for the Romanian language. The uttered words by several speakers which the system must recognize can be commands for a robot. The study aims to examine the performance of the system by minimizing the error.
Keywords :
human-robot interaction; natural language processing; neural nets; speech recognition; Romanian language; discriminant automatic speech recognition system; human-computer interaction; neural networks; robot; speakers; Feature extraction; Hidden Markov models; Neural networks; Speech; Speech processing; Speech recognition; Training; feature extraction; multilayer perceptrons; recurrent neural networks; speech processing; speech recognition;
Conference_Titel :
Development and Application Systems (DAS), 2014 International Conference on
Conference_Location :
Suceava
DOI :
10.1109/DAAS.2014.6842448
