Title
Exploring Fusion Methods And Feature Space For The Classification Of Paralinguistic Information
Abstract
This paper introduces the different systems developed by Aholab Signal Processing Laboratory for The INTERSPEECH 2017 Computational Paralinguistics Challenge. which includes three different subtasks: Addressee, Cold and Snoring classification. Several classification strategies and features related with the spectrum, prosody and phase have been tested separately and further combined by using different fusion techniques, such as early fusion by means of multi-feature vectors, late fusion of the standalone classifier scores and label fusion via weighted voting. The obtained results show that the applied fusion methods improve the performance of the standalone detectors and provide systems capable of outperforming the baseline systems in terms of UAR.
Year
DOI
Venue
2017
10.21437/Interspeech.2017-1378
18TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2017), VOLS 1-6: SITUATED INTERACTION
Keywords
Field
DocType
speech processing, classifier fusion, computational paralinguisties
Feature vector,Paralanguage,Pattern recognition,Computer science,Fusion,Speech recognition,Artificial intelligence
Conference
ISSN
Citations 
PageRank 
2308-457X
2
0.39
References 
Authors
0
7
Name
Order
Citations
PageRank
David Tavarez163.83
Xabier Sarasola231.78
Agustín Alonso373.54
Jon Sánchez416714.48
Luis Serrano531.75
Eva Navas630328.48
Inma Hernáez719621.64