Feature Selection for Improved Bandwidth Extension of Speech Signals

Authors:

Jax, P. ,  Vary, P.

Book Title:

Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

Volume:

1

Pages:

p.p. 697-700

Address:

Montreal, Canada

Date:

May. 2004

Language:

English

Abstract

The aim of artificial bandwidth extension (BWE) is to convert speech signals with "standard telephone" quality (frequencies up to 3.4 kHz) into 7 kHz wideband speech. The principal key to high quality BWE is the estimation of the spectral envelope of the wideband speech. In general, this estimation of the wideband spectral envelope is based on a number of features that are extracted from the narrowband input speech signal. In this paper we investigate potential features and evaluate their suitability for the BWE application. The quality of each feature is quantified in terms of the statistical measures of mutual information and separability. It turns out that the best BWE results are obtained by using a large feature "super-vector" (-> high mutual information) which is subsequently reduced in dimension by a linear discriminant analysis (-> large separability). This solution also helps to reduce the computational complexity of the estimation of the wideband spectral envelope.

Download

BibTeX

Copyright © by IKS
jax04a.pdf

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

---