Paper Info
Title
Application of non-negative frequency-weighted energy operator for vowel region detection.
Abstract
In this paper, a novel technique has been proposed for the vowel region detection from the continuous speech using an envelope of the derivative of the speech signal, which is a non-negative, frequency-weighted energy operator. The proposed vowel region detection method is implemented using a two-stage algorithm. The first stage of vowel region detection consists of speech signal analysis to detect vowel onset points (VOP) and vowel end-points (VEP) using an instantaneous energy contour obtained from the envelope of the derivative of a speech signal. The VOPs and VEPs are spotted using the peak-finding algorithm based upon the first order Gaussian differentiator. The next stage consists of removal of spurious vowel regions and the correction of hypothesized VOP and VEP locations using combined cues obtained from the uniformity of epoch intervals and strength of the excitation of the speech signal. Performance of the proposed method for detecting vowel regions from the speech signal is evaluated using TIMIT acoustic-phonetic speech corpus. The proposed approach resulted in significantly high detection rate and less false alarm rate compared to the state-of-the-art methods in both clean and noisy environments.
Year
DOI
Venue
2018
10.1007/s10772-018-9505-x
I. J. Speech Technology
Keywords
Field
DocType
Vowel onset point, Vowel end-point, Instantaneous energy contour, Envelope-derivative of the speech signal, Uniformity of epoch intervals, Strength of the excitation
Speech corpus,Signal processing,TIMIT,Pattern recognition,Energy operator,Computer science,Differentiator,Speech recognition,Negative frequency,Artificial intelligence,Vowel,Constant false alarm rate
Journal
Volume
Issue
ISSN
21
2
1381-2416
Citations 
PageRank 
References 
0
0.34
16
Authors
2
Name
Order
Citations
PageRank
Ramakrishna Thirumuru101.35
Anil Kumar Vuppala211316.31