Feature extraction with a multiscale modulation analysis for robust automatic speech recognition

In this work we present a new feature extraction method that is robust against the effects of varying vocal tract lengths. The principle of the method is based on invariant integration and makes use of a modulation filtering approach, similar to the recently proposed scattering transform. In particular, we show how the transform can be used to obtain features that are robust against variations of the vocal tract length. Phoneme recognition experiments show a clearly increased robustness in case of mismatching average vocal tract lengths.