The integral decode: A smoothing technique for robust HMM-based speaker recognition

IEEE Transactions on Speech and Audio Processing

Volumn 10, Issue 5, 2002, Pages 315-324

  Roch, Marie ^a,b,c,d   Hurtig, Richard R ^e  

^a IEEE   (United States)

^b University of Iowa   (United States)

^c The Department of Electrical and Computer Engineering   (United States)

^d SAN DIEGO STATE UNIVERSITY   (United States)

^e UNIVERSITY OF IOWA   (United States)

Author keywords

Hidden Markov model (HMM); Integral decode; Maximum a posteriori decision rule; Speaker recognition; Talker recognition; Text independent speaker identification

Indexed keywords

HIDDEN MARKOV MODELS (HMM);

ACOUSTIC NOISE; APPROXIMATION THEORY; COMPUTATIONAL METHODS; MARKOV PROCESSES; MATHEMATICAL MODELS;

SPEECH RECOGNITION;

EID: 0036649276     PISSN: 10636676     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSA.2002.800558     Document Type: Article

References (15)

1. Robust text-independent speaker identification using Gaussian mixture speaker models
2. A minimax classification approach with application to robust speech recognition
3. Robust speech recognition based on joint model and feature space optimization of hidden Markov models
4. A Bayesian predictive approach to robust speech recognition
5. Robust speech recognition based on a Bayesian prediction approach
6. On the asymptotic statistical behavior of empirical cepstral coefficients
7. A vector Taylor series approach for environment-independent speech recognition
8. Upper and lower bounds on the mean of noisy speech: Application to minimax classification