A speech signal captured by a distant microphone is generally contaminated by background noise, which severely degrades the audible quality and intelligibility of the observed signal. To resolve this issue, speech enhancement has been intensively studied. In this paper, we consider a text-informed speech enhancement, where the enhancement process is guided by the corresponding text information,...

Nonacoustic sensors such as the general electromagnetic motion sensor (GEMS), the physiological microphone (P-mic), and the electroglottograph (EGG) offer multimodal approaches to speech processing and speaker and speech recognition. These sensors provide measurements of functions of the glottal excitation and, more generally, of the vocal tract articulator movements that are relatively immune ...

Aiming at robust spoken dialogue interaction in motorcycle environment, we investigate various configurations for a speech front-end, which consists of speech pre-processing, speech enhancement and speech recognition components. These components are implemented as agents in the Olympus/RavenClaw framework, which is the core of a multimodal dialogue interaction interface of a wearable solution f...

A New system for speech enhancement, that uses hidden markov models (HMM) with noise-robust features, is developed. This system alleviates the error in decoding the noisy speech, that was observed in the conventional modelbased enhancement system [2] . This decoding error results in a degradation in the performance of the conventional system from its theoretical upper limits. A comparative test...

This paper proposes a novel method of speech enhancement that moves away from conventional filtering-based methods and instead aims to reconstruct clean speech from a set of speech features. Underlying the enhancement system is a speech model which at present is based on a sinusoidal model. This is driven by a set of speech features, comprising voicing, fundamental frequency and spectral envelo...