Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
A Maximum Likelihood Approach to Continuous Speech Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reconfigurable Computing for Speech Recognition: Preliminary Findings
FPL '00 Proceedings of the The Roadmap to Reconfigurable Computing, 10th International Workshop on Field-Programmable Logic and Applications
Stylized facts of financial time series and hidden semi-Markov models
Computational Statistics & Data Analysis
Structured Hidden Markov Model: A General Framework for Modeling Complex Sequences
AI*IA '07 Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing
Modeling Ant Activity by Means of Structured HMMs
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Analysis of Time-multiplexed Security Videos
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
hsmm - An R package for analyzing hidden semi-Markov models
Computational Statistics & Data Analysis
Variable duration motion texture for human motion modeling
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Additive and nonadditive fuzzy hidden Markov models
IEEE Transactions on Fuzzy Systems
Detecting and discriminating behavioural anomalies
Pattern Recognition
Modeling state durations in hidden Markov models for automatic speech recognition
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
Incorporating acoustic-phonetic knowledge in hybrid TDNN/HMM frameworks
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
On increasing structural complexity of finite state speech models
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
Use of semi-Markov models for speaker-independent phoneme recognition
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
A real-time recurrent error propagation network word recognition system
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
Modeling duration in a hidden Markov model with the exponential family
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: speech processing - Volume II
A segmental HMM for speech pattern modelling
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: speech processing - Volume II
Handwritten word recognition using continuous density variable duration hidden Markov model
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: image and multidimensional signal processing - Volume V
Unsupervised segmentation of hidden semi-Markov non-stationary chains
Signal Processing
International Journal of Speech Technology
Modeling timing structure in multimedia signals
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
A study on high-order hidden markov models and applications to speech recognition
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
Identifying and forecasting economic regimes in TAC SCM
AMEC'05 Proceedings of the 2005 international conference on Agent-Mediated Electronic Commerce: designing Trading Agents and Mechanisms
An efficient algorithm for parameterizing HsMM with Gaussian and Gamma distributions
Information Processing Letters
A hidden Markov model for collaborative filtering
MIS Quarterly
Exploring the latent segmentation space for the assessment of multiple change-point models
Computational Statistics
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During the past decade, the applicability of hidden Markov models (HMM) to various facets of speech analysis has been demonstrated in several different experiments. These investigations all rest on the assumption that speech is a quasi-stationary process whose stationary intervals can be identified with the occupancy of a single state of an appropriate HMM. In the traditional form of the HMM, the probability of duration of a state decreases exponentially with time. This behavior does not provide an adequate representation of the temporal structure of speech. The solution proposed here is to replace the probability distributions of duration with continuous probability density functions to form a continuously variable duration hidden Markov model (CVDHMM). The gamma distribution is ideally suited to specification of the durational density since it is one-sided and only has two parameters which, together, define both mean and variance. The main result is a derivation and proof of convergence of re-estimation formulae for all the parameters of the CVDHMM. It is interesting to note that if the state durations are gamma-distributed, one of the formulae is non-algebraic but, fortuitously, has properties such that it is easily and rapidly solved numerically to any desired degree of accuracy. Other results are presented including the performance of the formulae on simulated data.