Abstract
Analysis of speech signals is usually carried out using STFT. The most successful features currently being used in both speech recognition and speaker recognition systems are cepstral features. The cepstral features in one way or another are based on the source-filter model of speech production. However, it is well known that a significant part of the acoustic information cannot be modeled by the linear source-filter model. The source-filter model assumes that the sound source for the voiced speech is localized in the larynx and the vocal tract acts as a convolution filter for the emitted sound. Examples of phenomena not well-captured by the source-filter model include unstable airflow, turbulence and nonlinearities arising from oscillators with time-varying masses.
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Holambe, R.S., Deshpande, M.S. (2012). AM-FM: Modulation and Demodulation Techniques. In: Advances in Non-Linear Modeling for Speech Processing. SpringerBriefs in Electrical and Computer Engineering(). Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-1505-3_5
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DOI: https://doi.org/10.1007/978-1-4614-1505-3_5
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