Foundations of statistical natural language processing
Foundations of statistical natural language processing
Speech synthesis using stochastic Markov graphs
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02
Automatic Decision Making in SHM Using Hidden Markov Models
DEXA '07 Proceedings of the 18th International Conference on Database and Expert Systems Applications
Review: Statistical parametric speech synthesis
Speech Communication
Analysis of verbal and nonverbal acoustic signals with the dresden UASR system
COST 2102'07 Proceedings of the 2007 COST action 2102 international conference on Verbal and nonverbal communication behaviours
A specialized on-the-fly algorithm for lexicon and language model composition
IEEE Transactions on Audio, Speech, and Language Processing
COST'11 Proceedings of the 2011 international conference on Cognitive Behavioural Systems
A cortical approach based on cascaded bidirectional hidden markov models
COST'11 Proceedings of the 2011 international conference on Cognitive Behavioural Systems
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This paper describes an approach to intelligent signal processing. First we propose a general signal model which applies to speech, music, biological, and technical signals. We formulate this model mathematically using a unification of hidden Markov models and finite state machines. Then we name tasks for intelligent signal processing systems and derive a hierarchical architecture which is capable of solving them. We show the close relationship of our approach to cognitive dynamic systems. Finally we give a number of application examples.