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Time-frequency coherence for periodic-aperiodic decomposition of speech signals

Vijayan, K and Dhiman, JK and Seelamantula, CS (2017) Time-frequency coherence for periodic-aperiodic decomposition of speech signals. In: 18th Annual Conference of the International Speech Communication Association, INTERSPEECH 2017, 20 - 24 August 2017, Stockholm, pp. 329-333.

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Official URL: https://doi.org/10.21437/Interspeech.2017-726


Decomposing speech signals into periodic and aperiodic components is an important task, finding applications in speech synthesis, coding, denoising, etc. In this paper, we construct a time-frequency coherence function to analyze spectro-temporal signatures of speech signals for distinguishing between deterministic and stochastic components of speech. The narrowband speech spectrogram is segmented into patches, which are represented as 2-D cosine carriers modulated in amplitude and frequency. Separation of carrier and amplitude/frequency modulations is achieved by 2-D demodulation using Riesz transform, which is the 2-D extension of Hilbert transform. The demodulated AM component reflects contributions of the vocal tract to spectrogram. The frequency modulated carrier (FM-carrier) signal exhibits properties of the excitation. The time-frequency coherence is defined with respect to FM-carrier and a coherence map is constructed, in which highly coherent regions represent nearly periodic and deterministic components of speech, whereas the incoherent regions correspond to unstructured components. The coherence map shows a clear distinction between deterministic and stochastic components in speech characterized by jitter, shimmer, lip radiation, type of excitation, etc. Binary masks prepared from the time-frequency coherence function are used for periodic-aperiodic decomposition of speech. Experimental results are presented to validate the efficiency of the proposed method.

Item Type: Conference Paper
Publication: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Publisher: International Speech Communication Association
Additional Information: The copyright for this article belongs to the International Speech Communication Association.
Keywords: Audio signal processing; Decomposition; Demodulation; Frequency modulation; Mathematical transformations; Optical variables measurement; Signal processing; Spectrographs; Speech; Speech recognition; Speech synthesis; Stochastic systems, Coherence function; Hilbert transform; Riesz transform; Spectrograms; Temporal pattern, Speech communication
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 25 Jul 2022 05:01
Last Modified: 25 Jul 2022 05:01
URI: https://eprints.iisc.ac.in/id/eprint/74712

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