Speaker Independent Phonetic Recognition Using Auditory Modelling and Recurrent Neural Networks

Two speaker independent speech recognition experiments, regarding the automatic discrimination of the Italian alphabet I-set and E-set , two very difficult
Italian phonetic classes, will be described. The speech signal is analyzed by a recently developed joint synchrony/mean-rate auditory processing scheme and a
fully-connected feed-forward recurrent BP network was used for the classification stage. The achieved speaker independent mean recognition rate was 65%, for the I-
set and 88% for the E-set showing rather satisfactory results given the difficulty of both tasks.

Tipo Pubblicazione: 
Contributo in atti di convegno
Author or Creator: 
Cosi P.
Mian G.A.
Contolini M.
Source: 
ICANN-94, International Conference on Artificial Neural Networks, pp. 925–928, Sorrento, Italy, 26-29 May, 1994
Date: 
1994
Resource Identifier: 
http://www.cnr.it/prodotto/i/241576
https://dx.doi.org/10.1007/978-1-4471-2097-1
info:doi:10.1007/978-1-4471-2097-1
http://www.researchgate.net/publication/2510356_Speaker_Independent_Phonetic_Recognition_Using_Auditory_Modelling_And_Recurrent_Neural_Networks/file/60b7d518a074846b32.pdf
urn:isbn:978-3-540-19887-1
Language: 
Eng
ISTC Author: 
Ritratto di Piero Cosi
Real name: