Authors:
Maider Zamalloa
1
;
Mikel Penagarikano
1
;
Luis Javier Rodríguez-Fuentes
1
;
Germán Bordel
1
and
Juan Pedro Uribe
2
Affiliations:
1
University of the Basque Country, Spain
;
2
Ikerlan - Technological Research Center, Spain
Keyword(s):
Speaker tracking, Ambient intelligence, AMI Corpus.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Ambient Intelligence
;
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Conversational Agents
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Soft Computing
;
Symbolic Systems
Abstract:
Ambient intelligence is an interdisciplinary paradigm which envisages smart spaces that provide services and adapt transparently to the user. As the most natural interface for human interaction, speech can be exploited for adaptation purposes in such scenarios. Low latency is required, since adaptation must be continuous. Most speaker tracking approaches found in the literature work offline, fully processing pre-recorded audio files by a two-stage procedure: (1) performing acoustic segmentation and (2) assigning each segment a speaker label. In this work a real-time low-latency speaker tracking system is presented, which deals with continuous audio streams. Experimental results are reported on the AMI Corpus of meeting conversations, revealing the effectiveness of the proposed approach when compared to an offline speaker tracking system developed for reference.