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» Fitting hidden Markov models to psychological data
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NIPS
2008
13 years 10 months ago
Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM
Neural activity is non-stationary and varies across time. Hidden Markov Models (HMMs) have been used to track the state transition among quasi-stationary discrete neural states. W...
Kentaro Katahira, Jun Nishikawa, Kazuo Okanoya, Ma...
EMNLP
2004
13 years 10 months ago
Comparing and Combining Generative and Posterior Probability Models: Some Advances in Sentence Boundary Detection in Speech
We compare and contrast two different models for detecting sentence-like units in continuous speech. The first approach uses hidden Markov sequence models based on N-grams and max...
Yang Liu, Andreas Stolcke, Elizabeth Shriberg, Mar...
INTERSPEECH
2010
13 years 3 months ago
An intonation model for TTS in sepedi
We present an initial investigation into the acoustic realisation of tone in continuous utterances in Sepedi (a language in the Southern Bantu family). An analytic model for the g...
Daniel R. van Niekerk, Etienne Barnard
FGR
1998
IEEE
203views Biometrics» more  FGR 1998»
14 years 1 months ago
Automated Facial Expression Recognition Based on FACS Action Units
Automated recognition of facial expression is an important addition to computer vision research because of its relevance to the study of psychological phenomena and the developmen...
James Jenn-Jier Lien, Takeo Kanade, Jeffrey F. Coh...
AAAI
1997
13 years 10 months ago
The "Inverse Hollywood Problem": From Video to Scripts and Storyboards via Causal Analysis
We address the problem of visually detecting causal events and tting them together into a coherent story of the action witnessed by the camera. We show that this can be done by re...
Matthew Brand