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Fine structure spectrography and its application in speech.

Hilmi R Dajani·Willy Wong·Hans Kunov
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Abstract

A filterbank-based algorithm for time-varying spectral analysis is proposed. The algorithm, which is an enhanced realization of the conventional spectrogram, consists of hundreds or thousands of highly overlapping wideband filter/detector stages, followed by a peak detector that probes the filter/detector outputs at very short time intervals. Analysis with synthetic modulated signals illustrates how the proposed method demodulates these signals. The resulting spectrogram-like display, referred to as a "fine structure spectrogram," shows the fine structure of the modulations in substantially higher detail than is possible with conventional spectrograms. Error evaluation is performed as a function of various parameters of a single- and two-component synthetic modulated signal, and of parameters of the analysis system. In speech, the fine structure spectrogram can detect small frequency and amplitude modulations in the formants. It also appears to identify additional significant time-frequency components in speech that are not detected by other methods, making it potentially useful in speech processing applications.

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AlgorithmsHumansPhoneticsSensitivity and SpecificitySound SpectrographySpeech AcousticsJournal ArticleResearch Support, Non-U.S. Gov't

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Hilmi R Dajani, Willy Wong, Hans Kunov. 2005. Fine structure spectrography and its application in speech.. https://doi.org/10.1121/1.1896365

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