Robust clustering - based realtime vowel recognition

In the therapy of the hearing impaired one of the key problems is how to deal with the lack of proper auditive feedback which impedes the development of intelligible speech. The effectiveness of the therapy relies heavily on accurate phoneme recognition. Because of the environmental difficulties, si...

Teljes leírás

Elmentve itt :
Bibliográfiai részletek
Szerzők: Paczolay Dénes
Bánhalmi András
Kocsor András
Testületi szerző: Conference for PhD Students in Computer Science (5.) (2006) (Szeged)
Dokumentumtípus: Cikk
Megjelent: 2008
Sorozat:Acta cybernetica 18 No. 3
Kulcsszavak:Számítástechnika, Kibernetika
Tárgyszavak:
Online Access:http://acta.bibl.u-szeged.hu/12829
LEADER 01824nab a2200253 i 4500
001 acta12829
005 20220616153354.0
008 161015s2008 hu o 0|| eng d
022 |a 0324-721X 
040 |a SZTE Egyetemi Kiadványok Repozitórium  |b hun 
041 |a eng 
100 1 |a Paczolay Dénes 
245 1 0 |a Robust clustering - based realtime vowel recognition  |h [elektronikus dokumentum] /  |c  Paczolay Dénes 
260 |c 2008 
300 |a 451-462 
490 0 |a Acta cybernetica  |v 18 No. 3 
520 3 |a In the therapy of the hearing impaired one of the key problems is how to deal with the lack of proper auditive feedback which impedes the development of intelligible speech. The effectiveness of the therapy relies heavily on accurate phoneme recognition. Because of the environmental difficulties, simple recognition algorithms may have a weak classification performance, so various techniques such as normalization and classifier combination are applied to raising the overall recognition accuracy. In earlier work we came to realise that the classification accuracy is higher on a database that is manually clustered according to the gender and age of the speakers. This paper examines what happens when we cluster the database into a few groups automatically and then we train separate classifiers for each cluster. The results shows that this two-step method can increase the recognition performance by several percent. 
650 4 |a Természettudományok 
650 4 |a Számítás- és információtudomány 
695 |a Számítástechnika, Kibernetika 
700 0 1 |a Bánhalmi András  |e aut 
700 0 1 |a Kocsor András  |e aut 
710 |a Conference for PhD Students in Computer Science (5.) (2006) (Szeged) 
856 4 0 |u http://acta.bibl.u-szeged.hu/12829/1/Paczolay_2008_ActaCybernetica.pdf  |z Dokumentum-elérés