Automatic speech recognition of cochlear implant-like spectrally reduced speech
Résumé
In this paper, we investigate the behavior of automatic speech recognition (ASR) system with cochlear implant-like spectrally reduced speech (SRS). The SRSs have been synthesized by using amplitude modulation (AM) and frequency modulation(FM) components extracted by using the frequency amplitude
modulation encoding (FAME) strategy. In fact, three sets of SRS were synthesized, one by using only AM components and the two others by using both AM and FM components, but with or without subtraction of rapidly varying FM components. Therefore, along with investigating the behavior of ASR using
SRS, we investigate the effect of subtracting rapidly varying FM components of SRS in ASR. Recognition results show that even though slowly varying FM components are useful to support human speech recognition, they bring no significant improvement in ASR when the SRS spectral resolution is sufficiently good. The TIDIGITS speech database and HTK speech recognition software were used for the experimentations.