Automatic sound classification for improving speech intelligibility in hearing aids using a layered structure

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4224 LNCS, Issue , 2006, Pages 306-313

  Alexandre, Enrique ^a   Cuadra, Lucas ^a   Álvarez, Lorena ^a   Rosa Zurera, Manuel ^a   López Ferreras, Francisco ^a  

^a UNIVERSITY OF ALCALÁ   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; HEARING AIDS; NEURAL NETWORKS; SPEECH INTELLIGIBILITY; SPURIOUS SIGNAL NOISE;

AUTOMATIC SOUND CLASSIFICATION; CLASSIFICATION ALGORITHMS; LAYERED STRUCTURES;

CLASSIFICATION (OF INFORMATION);

EID: 33750551695     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11875581_37     Document Type: Conference Paper

References (17)

1. Keidser, G.: The relationships between listening conditions and alterative amplification schemes for multiple memory hearing aids. Ear Hear 16 (1995) 575-586
2. Keidser, G.: Selecting different amplification for different listening conditions. J. of the American Academy of Audiology 7 (1996) 92-104
3. Büchler, M.: Algorithms for sound classification in hearing instruments. PhD thesis, Swiss Federal Institute of Technology, Zurich (2002)
4. Nordqvist, P., Leijon A.: An efficient robust sound classification algorithm for hearing aids. J. Acoustic Soc. Am. 115(6) (2004) 3033-3041
5. Alexandre, E., Rosa, M., Cuadra, L., Gil-Pita, R.: Application of Fisher linear discriminant analysis to speech/music classification. In: AES 120th Convention. (2006)
6. Guaus, E., Batlle, E.: A non-linear rhythm-based style classification for broadcast speech-music discrimination. In: AES 116th Convention. (2004)
7. Lu, L., Zhang, H.J., Jiang, H.: Content analysis for audio classification and segmentation. IEEE Transactions on speech and audio processing 10(7) (2002) 504-516
8. Scheirer, E., Slaney, M.: Construction and evaluation of a robust multifeature speech/music discriminator. In: ICASSP. (1997)
9. Davis, S., Mermelstein, P.: Experiments in syllable-based recognition of continuous speech. IEEE Transactions on Acoustics, Speech and Signal Processing 28 (1980) 357-366
10. Logan, B.: Mel frequency cepstral coefficients for music modeling. In: Int. Symp. Music Information Retrieval (ISMIR). (2000)
11. Tzanetakis, G., Cook, P.: Musical genre classification of audio signals. IEEE Transactions on speech and audio processing 10(5) (2002) 293-302
12. Saunders, J.: Real time discrimination of broadcast speech/music. In: ICASSSP. (1996) 993-996
13. ITU-T: Objective measurement of active speech level. Recommendation P.56 (1993)
14. Batlle, E., Neuschmied, H., Uray, P., Ackerman, G.: Recognition and analysis of audio for copyright protection: the RAA project. Journal of the American Society for Information Science and Technology 55(12) (2004) 1084-1091
15. Fisher, R.: The use of multiple measurements in taxonomic problems. Annals of Eugenics (7) (1936) 179-188
16. Haykin, S.: Neural Networks: A comprehensive foundation. Prentice Hall (1999)
17. Jain, A.K., Duin, R.P., Mao, J.: Statistical pattern recognition: a review. IEEE Transactions on pattern analysis and machine intelligence 22(1) (2000) 4-37