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ICASSP
2008
IEEE
14 years 3 months ago
Exploiting contextual information for improved phoneme recognition
In this paper, we investigate the significance of contextual information in a phoneme recognition system using the hidden Markov model - artificial neural network paradigm. Cont...
Joel Pinto, B. Yegnanarayana, Hynek Hermansky, Mat...
ICMCS
2006
IEEE
197views Multimedia» more  ICMCS 2006»
14 years 3 months ago
Identify Sports Video Shots with "Happy" or "Sad" Emotions
Semantic video content extraction and selection are critical steps in sports video analysis and editing. The identification of video segments can be from various semantic perspec...
Jinjun Wang, Engsiong Chng, Changsheng Xu, Hanqing...
ICDAR
2003
IEEE
14 years 2 months ago
Optimizing the Number of States, Training Iterations and Gaussians in an HMM-based Handwritten Word Recognizer
In off-line handwriting recognition, classifiers based on hidden Markov models (HMMs) have become very popular. However, while there exist well-established training algorithms, s...
Simon Günter, Horst Bunke
ACL
2009
13 years 7 months ago
ProLiV - a Tool for Teaching by Viewing Computational Linguistics
ProLiV - Animated Process-modeler of Complex (Computational) Linguistic Methods and Theories - is a fully modular, flexible, XML-based stand-alone Java application, used for compu...
Monica Gavrila, Cristina Vertan
ICASSP
2009
IEEE
13 years 7 months ago
Phoneme cluster based state mapping for text-independent voice conversion
This paper takes phonetic information into account for data alignment in text-independent voice conversion. Hidden Markov Models are used for representing the phonetic structure o...
Meng Zhang, Jiaohua Tao, Jani Nurminen, Jilei Tian...