ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

Comparative study of filter-bank mean-energy distance for automated segmentation of speech signals

Ananthakrishnan, G and Ranjani, HG and Ramakrishnan, AG (2006) Comparative study of filter-bank mean-energy distance for automated segmentation of speech signals. In: International Conference on Signal Processing, Communications and Networks,, Feb 22-24, 2007, Chennai, India, pp. 6-10.

[img] PDF
04156573.pdf - Published Version
Restricted to Registered users only

Download (4Mb) | Request a copy
Official URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumb...

Abstract

This paper describes a method of automated segmentation of speech assuming the signal is continuously time varying rather than the traditional short time stationary model. It has been shown that this representation gives comparable if not marginally better results than the other techniques for automated segmentation. A formulation of the 'Bach' (music semitonal) frequency scale filter-bank is proposed. A comparative study has been made of the performances using Mel, Bark and Bach scale filter banks considering this model. The preliminary results show up to 80 % matches within 20 ms of the manually segmented data, without any information of the content of the text and without any language dependence. 'Bach' filters are seen to marginally outperform the other filters.

Item Type: Conference Paper
Additional Information: Copyright 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 02 Sep 2010 05:16
Last Modified: 19 Sep 2010 06:12
URI: http://eprints.iisc.ernet.in/id/eprint/30530

Actions (login required)

View Item View Item