Relevancy of time-frequency features for phonetic classification measured by mutual information
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01
Discrete-time speech signal processing: principles and practice
Discrete-time speech signal processing: principles and practice
Spectrum restoration from multiscale auditory phase singularities by generalized projections
IEEE Transactions on Audio, Speech, and Language Processing
Discrimination of speech from nonspeech based on multiscale spectro-temporal Modulations
IEEE Transactions on Audio, Speech, and Language Processing
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In this work, we adopt an information theoretic approach - the Information Bottleneck method - to extract the relevant modulation frequencies across both dimensions of a spectrogram, for speech / non-speech discrimination (music, animal vocalizations, environmental noises). A compact representation is built for each sound ensemble, consisting of the maximally informative features. We demonstrate the effectiveness of a simple thresholding classifier which is based on the similarity of a sound to each characteristic modulation spectrum.