Paper Info
Title
Adaptive phoneme alignment based on rough set theory
Abstract
The current work describes a phoneme matching algorithm based on rough set concepts. The objective of this type of algorithms is focused on the localization of the phonemic content of a specific spoken occurrence. According to the proposed algorithm, a number of rough sets containing the multiple expected phonemic instances in a sequence are created, each defined by a set of short term frames of the voice signal. The properties of the corresponding information system are derived from a features set calculated from the speech signal upon initiation. Given the above, an iterative procedure is applied by updating the phoneme instances versus the optimization of the accuracy metric. The main advantage of this algorithm is the absence of a training phase allowing for wider speaker adaptability and independency. The current paper focuses on the feasibility of the task as this work is still in early research stage.
Year
DOI
Venue
2010
10.1007/978-3-642-13529-3_12
RSCTC
Keywords
Field
DocType
rough set concept,phonemic content,current paper,rough set theory,rough set,speech signal,phoneme matching algorithm,multiple expected phonemic instance,phoneme instance,current work,proposed algorithm,adaptive phoneme alignment,information system
Information system,Adaptability,Pattern recognition,Rough set,Speech recognition,Artificial intelligence,Mathematics,Blossom algorithm
Conference
Volume
ISSN
ISBN
6086
0302-9743
3-642-13528-5
Citations 
PageRank 
References 
2
0.38
12
Authors
4
Name
Order
Citations
PageRank
Konstantinos Avdelidis1201.66
Charalampos Dimoulas210412.35
G. Kalliris327714.72
George Papanikolaou4807.07