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A non-linear operator based method for harmonic feature extraction from speech signals
Kavanagh, Darren F.; Boland, Frank
Paper presented at the IEEE International Conference on Signal Processing and Communications (ICSPC 2007), 24-27 November 2007, Dubai, United Arab Emirates 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. Irish Research Council for Science, Engineering and Technology Charles Parsons Energy Research Awards Charles Parson ti, pe, la, sp, ke, ab, co - kpw10/11/11
Keyword(s): Teager energy operator (TEO).; Harmonic; Feature; Extraction; Classification; Harmonic analysis; Automatic speech recognition; Pattern recognition systems; Signal processing
Publication Date:
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: University College Dublin
Publisher(s): IEEE
File Format(s): other; application/pdf; text/plain
First Indexed: 2012-08-25 05:17:01 Last Updated: 2018-10-11 16:17:44