This study is concerned with the challenge of automatically segregating a target speech signal from interfering background noise. A computational speech segregation system is presented which exploits logarithmically-scaled amplitude modulation spectrogram (AMS) features to distinguish between speech and noise activity on the basis of individual time-frequency (T-F) units. One important parameter of the segregation system is the window duration of the analysis-synthesis stage, which determines the lower limit of modulation frequencies that can be represented but also the temporal acuity with which the segregation system can manipulate individual T-F units. To clarify the consequences of this trade-off on modulation-based speech segregation performance, the influence of the window duration was systematically investigated.
Bibliographic reference. May, Tobias / Bentsen, Thomas / Dau, Torsten (2015): "The role of temporal resolution in modulation-based speech segregation", In INTERSPEECH-2015, 170-174.