Automatic speech recognition (ASR) in reverberant environments is a challenging task. Most
dereverberation techniques address this problem through signal processing and enhances …

Speech is one of the most natural medium for human communication, which makes it vital to
human-robot interaction. In real environments where robots are deployed, distant-talking …

Speech enhancement is a common approach to address the effects of degradation due to
noise and channel contamination. This approach is intended to suppress unwanted signal …

This paper addresses the problem of time-varying channels in speech-recognition-based
human-robot interaction using Locally-Normalized Filter-Bank features (LNFB), and training …

Speech recognition under reverberant condition is a difficult task. Most dereverberation
techniques used to address this problem enhance the reverberant waveform independent …

The acoustical dynamics of reverberation in an enclosed environment poses a problem to
human-robot communication. Any change in the azimuthal orientation of the speaker …

It is easy for human beings to discern whether an observed acoustic signal is a direct
speech, reflected speech or noise through simple listening. Relying purely on acoustic cues …

The paper addresses a robust wavelet-based speech enhancement for automatic speech
recognition in reverberant and noisy conditions. We propose a novel scheme in improving …

Acoustic reflection inside an enclosed environment is detrimental to human-robot
interaction. Reflection may manifest as phantom sources emanating from unknown …

This paper presents an improved wavelet-based dereverberation method for automatic
speech recognition (ASR). Dereverberation is based on filtering reverberant wavelet …