Multi‐objective optimisation of wavelet features for phoneme recognition-Reference-Cited by-同舟云学术

Multi‐objective optimisation of wavelet features for phoneme recognition

Published:2016-08 Issue:6 Volume:10 Page:685-691
ISSN:1751-9675
Container-title:IET Signal Processing
language:en
Short-container-title:IET signal process.

Author:

Vignolo Leandro Daniel¹,Rufiner Hugo Leonardo¹²,Milone Diego Humberto¹

Affiliation:

1. Research Institute for Signals, Systems and Computational Intelligence, sinc(i)FICH‐UNL/CONICET, Ciudad Universitaria UNL(S3000) Santa FeArgentina

2. Laboratorio de Cibernética FI‐UNER(E3100) Oro Verde, Entre RíosArgentina

Funder

Universidad Nacional del Litoral

Fondo para la Investigación Científica y Tecnológica

Consejo Nacional de Investigaciones Científicas y Técnicas

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Signal Processing

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-spr.2015.0568

Reference40 articles.

1. Ratanpara T. Patel N.: ‘Singer identification using MFCC and LPC coefficients from Indian video songs’.Proc. 49th Annual Convention of the Computer Society of India (CSI) 2015 vol.1 pp.275–282 doi:https://doi.org/10.1007/978‐3‐319‐13728‐5_31

2. Comparative study of automatic speech recognition techniques

3. RASTA processing of speech

4. Computational Intelligence in Speech and Audio Processing: Recent Advances

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