Information fusion for subband-HMM speaker recognition

Proceedings of the International Joint Conference on Neural Networks

Volumn 2, Issue , 2001, Pages 1504-1509

  Higgins, J E ^a   Damper, R I ^a   Dodd, T J ^a  

^a UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CONSTRAINT THEORY; DATABASE SYSTEMS; MARKOV PROCESSES; MAXIMUM LIKELIHOOD ESTIMATION; MULTILAYER NEURAL NETWORKS; NATURAL FREQUENCIES; TEXT PROCESSING;

AUTOMATIC RELEVANCE DETERMINATION; HIDDEN MARKOV MODELLING; NARROWBAND NOISE; SPEAKER RECOGNITION;

SPEECH RECOGNITION;

EID: 0034875330     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (25)

1. Effectiveness of linear prediction characteristics of the speech wave for automatic speaker identification and verification
2. Subband approach for automatic speaker recognition: Optimal division of the frequency domain
3. Subband architecture for automatic speaker recognition
4. A new ASR approach based on independent processing and recombination of partial frequency bands
5. Speaker recognition: A tutorial
6. Speaker recognition - identifying people by their voices
7. Text-dependent speaker recognition using sub-band processing
8. An analysis of long-term variation of feature parameters of speech and its application to talker recognition
9. Cepstral analysis techniques for automatic speaker verification
10. Recent advances in speaker recognition
11. A multi-spectral data-fusion approach to speaker recognition
12. The evidence framework applied to classification problems
13. The full-combination sub-bands approach to noise robust HMM/ANN-based ASR
14. A recombination strategy for multi-band speech recognition based on mutual information criterion
15. Information fusion by humans and machines
16. Bayesian neural networks for classification: How useful is the evidence framework?
17. A tutorial on hidden Markov models and selected applications in speech recognition
18. Robust text-independent speaker identification using Gaussian mixture models
19. Sub-band speaker verification using dynamic recombination weights
20. The relation of pitch to frequency: A revised scale
21. Sub-band based recognition of noisy speech