A Multi-sensor Speech Database with Applications towards Robust Speech Processing in hostile Environments

9606

Authors

nan

Abstract

AbstractIn this paper, we present a database with speech in different types of background noises. The speech and noise were recorded with a set of different microphones and including some sensors that pick up the speech vibrations by making contact with the skull, the throat and the ear canal, respectively. As these sensors should be less sensitive to noise sources, our database can be especially useful for investigating the properties of these special microphones and comparing them to those of conventional microphones for applications requiring noise robust speech capturing and processing. In this paper we describe some experiments that were carried out using this database in the field of Voice Activity Detection (VAD). It is shown that the signals of a special microphone such as the throat microphone exhibit a high signal to noise ratio and that this property can be exploited to significantly improve the accuracy of a VAD algorithm.

Keywords

nan

Full Content

nan

Labeled Text

AbstractIn this paper, we present a database with speech in different types of background noises. The speech and noise were recorded with a set of different microphones and including some sensors that pick up the speech vibrations by making contact with the skull, the throat and the ear canal, respectively. As these sensors should be less sensitive to noise sources, our database can be especially useful for investigating the properties of these special microphones and comparing them to those of conventional microphones for applications requiring noise robust speech capturing and processing. In this paper we describe some experiments that were carried out using this database in the field of Voice Activity Detection (VAD). It is shown that the signals of a special microphone such as the throat microphone exhibit a high signal to noise ratio and that this property can be exploited to significantly improve the accuracy of a VAD algorithm.

Publication Details

Paper ID:
9606
Year:
2008
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan