A non-linear operator based method for harmonic feature extraction from speech signals

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Title: A non-linear operator based method for harmonic feature extraction from speech signals
Authors: Kavanagh, Darren F.
Boland, Frank
Permanent link: http://hdl.handle.net/10197/3336
Date: Nov-2007
Abstract: An important pre-processing stage in speech recognition systems is that of extracting phonetically pertinent acoustic features from the speech signal. These features form the basis for discriminative classification and serve as cues for the identification of phonetic events in speech. The paper addresses this by presenting a novel method for the classification of harmonic (short-term periodic) and non-harmonic segments in speech signals. Classification is accomplished by proposing two new features derived from the non-linear Teager energy operator (TEO). The features proposed are the TEO-Weighted Harmonic Product (TEO-WHP*)and the TEO-Weighted Harmonic Sum (TEO-WHS*). Experiments are reported and discussed that demonstrate the effectiveness and the importance of these features as a valuable preprocessor for many speech systems.
Funding Details: Irish Research Council for Science, Engineering and Technology
Type of material: Conference Publication
Publisher: IEEE
Copyright (published version): 2007 IEEE
Keywords: Teager energy operator (TEO).;Harmonic;Feature;Extraction;Classification
Subject LCSH: Harmonic analysis
Automatic speech recognition
Pattern recognition systems
Signal processing
DOI: 10.1109/ICSPC.2007.4728294
Language: en
Status of Item: Not peer reviewed
Is part of: IEEE International Conference on Signal Processing and Communications, 2007. ICSPC 2007 [proceedings]
Conference Details: Paper presented at the IEEE International Conference on Signal Processing and Communications (ICSPC 2007), 24-27 November 2007, Dubai, United Arab Emirates
Appears in Collections:ERC Research Collection
Electrical and Electronic Engineering Research Collection

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