Title
Co-training succeeds in Computational Paralinguistics
Abstract
Data sparsity is one of the major bottlenecks in the field of Computational Paralinguistics. Partially supervised learning approaches can help leverage this problem without the need of cost-intensive human labelling efforts. We thus investigate the feasibility of cotraining for exemplary paralinguistic speech analysis tasks spanning along the time-continuum: from short-term-related emotion to mid-term-related sleepiness and finally to long-term trait of gender. By dividing the acoustic feature space with two views as independent and sufficient as possible, the semi-supervised learning approach of co-training selects instances with high confidence scores in each view, and agglomerates them along with their predictions into initial training sets per iteration. Our experimental results on official Interspeech Computational Paralinguistics Challenge tasks effectively demonstrate co-training's superiority over the baseline formed by single-view self-training, especially for the short- and medium-term tasks emotion and sleepiness recognition.
Year
DOI
Venue
2013
10.1109/ICASSP.2013.6639325
ICASSP
Keywords
Field
DocType
computational paralinguistics,computational linguistics,sleepiness recognition,exemplary paralinguistic speech analysis,co-training,learning (artificial intelligence),short-term-related emotion,single-view self-training,short-term tasks emotion,co-training superiority,sleepiness,speech synthesis,data sparsity,iteration,emotion,medium-term tasks emotion,partially supervised learning,acoustic feature space,semi-supervised learning approach,semi-supervised learning,gender,iterative methods,midterm-related sleepiness,sleep,speech,databases,acoustics,semi supervised learning,learning artificial intelligence
Speech synthesis,Feature vector,Paralanguage,Iterative method,Computer science,Computational linguistics,Co-training,Supervised learning,Speech recognition,Artificial intelligence,Machine learning
Conference
ISSN
Citations 
PageRank 
1520-6149
7
0.45
References 
Authors
19
3
Name
Order
Citations
PageRank
Zixing Zhang139731.73
Jun Deng227818.59
Björn Schuller36749463.50