Paper Info
Title
Convex Weighting Criteria for Speaking Rate Estimation
Abstract
Speaking rate estimation directly from the speech waveform is a long-standing problem in speech signal processing. In this paper, we pose the speaking rate estimation problem as that of estimating a temporal density function whose integral over a given interval yields the speaking rate within that interval. In contrast to many existing methods, we avoid the more difficult task of detecting individual phonemes within the speech signal and we avoid heuristics such as thresholding the temporal envelope to estimate the number of vowels. Rather, the proposed method aims to learn an optimal weighting function that can be directly applied to time-frequency features in a speech signal to yield a temporal density function. We propose two convex cost functions for learning the weighting functions and an adaptation strategy to customize the approach to a particular speaker using minimal training. The algorithms are evaluated on the TIMIT corpus, on a dysarthric speech corpus, and on the ICSI Switchboard spontaneous speech corpus. Results show that the proposed methods outperform three competing methods on both healthy and dysarthric speech. In addition, for spontaneous speech rate estimation, the result show a high correlation between the estimated speaking rate and ground truth values.
Year
DOI
Venue
2015
10.1109/TASLP.2015.2434213
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
Keywords
Field
DocType
speaking rate estimation,convex optimization,dysarthria,speaker adaptation,vowel density function
Speech corpus,TIMIT,Weighting,Pattern recognition,Computer science,Speech recognition,Heuristics,Artificial intelligence,Thresholding,Convex optimization,Probability density function,Dysarthria
Journal
Volume
Issue
ISSN
23
9
2329-9290
Citations 
PageRank 
References 
5
0.46
15
Authors
4
Name
Order
Citations
PageRank
Yishan Jiao1102.61
Visar Berisha27622.38
Ming Tu3113.30
Julie Liss4105.98