Paper Info
Title
Ubiquitous and Robust Text-Independent Speaker Recognition for Home Automation Digital Life
Abstract
This paper presents a ubiquitous and robust text-independent speaker recognitionarchitecture for home automation digital life. In this architecture, a multiple microphone configuration is adopted to receive the pervasive speech signals. The multi-channel speech signals are then added together with a mixer. In a ubiquitous computing environment, the received speech signal is usually heavily corrupted by background noises. An SNR-aware subspace speech enhancement approach is used as a pre-processing to enhance the mixed signal. Considering the text-independent speaker recognition, this paper applies a multi-class support vectors machine (SVM)[10][11] instead of conventional Gaussian mixture models (GMMs)[12]. In our experiments, the speaker recognition rate can averagely reach 97.2% with the proposed ubiquitous speaker recognitionarchitecture.
Year
DOI
Venue
2008
10.1007/978-3-540-69293-5_24
UIC
Keywords
Field
DocType
text-independent speaker recognition,snr-aware subspace speech enhancement,pervasive speech signal,mixed signal,multi-channel speech signal,speech signal,proposed ubiquitous speaker recognitionarchitecture,ubiquitous computing environment,speaker recognition rate,robust text-independent speaker recognitionarchitecture,home automation digital life,robust text-independent speaker recognition,gaussian mixture model,home automation,speaker recognition,support vector machine
Speech enhancement,Speech processing,Computer science,Support vector machine,Home automation,Speech recognition,Speaker recognition,Speaker diarisation,Ubiquitous computing,Microphone
Conference
Volume
ISSN
Citations 
5061
0302-9743
4
PageRank 
References 
Authors
0.58
11
4
Name
Order
Citations
PageRank
Jhing-fa Wang1982114.31
Ta-Wen Kuan2376.59
Jia-Chang Wang351.30
Gaung-Hui Gu4221.85