An HMM-Based Approach for Off-Line Unconstrained Handwritten Word Modeling and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Speech Recognition: The Development of the Sphinx Recognition System
Automatic Speech Recognition: The Development of the Sphinx Recognition System
Content-Based Classification, Search, and Retrieval of Audio
IEEE MultiMedia
Dissimilarity representations allow for building good classifiers
Pattern Recognition Letters
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Maximum Entropy Markov Models for Information Extraction and Segmentation
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Emotions, speech and the ASR framework
Speech Communication - Special issue on speech and emotion
The production and recognition of emotions in speech: features and algorithms
International Journal of Human-Computer Studies - Application of affective computing in human—Computer interaction
On the structure of hidden Markov models
Pattern Recognition Letters
Online Handwriting Recognition for Tamil
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Structure-Based Statistical Features and Multivariate Time Series Clustering
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Emotion Recognition Based on Physiological Changes in Music Listening
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model Based Clustering of Audio Clips Using Gaussian Mixture Models
ICAPR '09 Proceedings of the 2009 Seventh International Conference on Advances in Pattern Recognition
Variational Gaussian Mixture Models for Speech Emotion Recognition
ICAPR '09 Proceedings of the 2009 Seventh International Conference on Advances in Pattern Recognition
Maximum entropy direct models for speech recognition
IEEE Transactions on Audio, Speech, and Language Processing
Temporal Feature Integration for Music Genre Classification
IEEE Transactions on Audio, Speech, and Language Processing
Content-based audio classification and retrieval by support vector machines
IEEE Transactions on Neural Networks
Classification of Multi-variate Varying Length Time Series Using Descriptive Statistical Features
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
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Modeling time series data of varying length is important in different domains. There are two paradigms for modeling the varying length sequential data. Tasks such as speech recognition need modeling the temporal dynamics and the correlations among the features. Hidden Markov models (HMM) are used for these tasks. In tasks such as speaker recognition, audio classification and speech emotion recognition, modeling the temporal dynamics is not critical. Gaussian mixture models (GMM) are commonly used for these tasks. Generative models such as HMMs and GMMs focus on estimating the density of the data and are not suitable for classifying the data of confusable classes. Discriminative classifiers such as support vector machines (SVM) are suitable for the fixed dimensional patterns. In this paper, we propose a hybrid framework where a generative front end is used for representing the varying length time series data and then a discriminative model is used for classification. A score based approach and a segment modeling based approach are proposed in this framework. Both the approaches are applied for speech emotion recognition. The performance is compared with that of an SVM classifier that uses different statistical features and also with that of the GMM classifiers that use maximum likelihood method and the variational Bayes method for parameter estimation. Both the proposed approaches outperform the methods used for comparison.