An acoustic-phonetic expert for analysis and processing of continuous speech in hindi. - P. Eswar; S. K. Gupta; C. Chandra Sekhar; B. Yegnanarayana 001; K. Nagamma Reddy (ECST, 1987)

Parsing spoken utterances in an inflectional language. - M. Prakash 002; G. V. Ramana Rao; C. Chandra Sekhar; B. Yegnanarayana 001 (EUROSPEECH, 1989)

Synthesizing intonation for speech in hindi. - A. S. Madhukumar; S. Rajendran; C. Chandra Sekhar; B. Yegnanarayana 001 (EUROSPEECH, 1991)

Neural network models for spotting stop consonant-vowel (SCV) segments in continuous speech. - C. Chandra Sekhar; B. Yegnanarayana 001 (ICNN, 1996)

A Residue Number Arithmetic based Circuit for Pipelined Computation of Autocorrelation Coefficients of Speech Signal. - Ansgar Drolshagen; Walter Anheier; C. Chandra Sekhar (VLSI Design, 1998)

Recognition of consonant-vowel utterances using Support Vector Machines. - Chellu Chandra Sekhar; Kazuya Takeda; Fumitada Itakura (ESANN, 2001)

Close-Class-Set Discrimination Method for Recognition of Stop_Consonant-Vowel Utterances Using Support Vector Machines. - Chellu Chandra Sekhar; Kazuya Takeda; Fumitada Itakura (ICANN, 2001)

Recognition of continuous speech segments of monophone units using support vector machines. - Weifeng Lee; C. Chandra Sekhar; Kazuya Takeda; Fumitada Itakura (INTERSPEECH, 2002)

Recognition of Consonant-Vowel (CV) Units of Speech in a Broadcast News Corpus Using Support Vector Machines. - Chellu Chandra Sekhar; Kazuya Takeda; Fumitada Itakura (SVM, 2002)

A constraint satisfaction model for recognition of stop consonant-vowel (SCV) utterances. - C. Chandra Sekhar; B. Yegnanarayana 001 (IEEE Trans. Speech Audio Process., 2002)

Constraint satisfaction model for enhancement of evidence in recognition of consonant-vowel utterances. - Suryakanth V. Gangashetty; C. Chandra Sekhar; B. Yegnanarayana 001 (ICASSP (2), 2003)

Combining evidence from multiple modular networks for recognition of consonant-vowel units of speech. - Suryakanth V. Gangashetty; K. Sreenivasa Rao; A. Nayeemulla Khan; C. Chandra Sekhar; Bayya Yegnanarayana (IJCNN, 2003)

Kernel Based Clustering for Multiclass Data. - D. Srikrishna Satish; C. Chandra Sekhar (ICONIP, 2004)

A Fast and Efficient Face Detection Technique Using Support Vector Machine. - R. Suguna; N. Sudha; C. Chandra Sekhar (ICONIP, 2004)

Acoustic model combination for recognition of speech in multiple languages using support vector machines. - Suryakanth V. Gangashetty; Chellu Chandra Sekhar; Bayya Yegnanarayana (IJCNN, 2004)

Detection of vowel on set points in continuous speech using autoassociative neural network models. - Suryakanth V. Gangashetty; Chellu Chandra Sekhar; B. Yegnanarayana 001 (INTERSPEECH, 2004)

Spotting Multilingual Consonant-Vowel Units of Speech Using Neural Network Models. - Suryakanth V. Gangashetty; C. Chandra Sekhar; B. Yegnanarayana 001 (NOLISP, 2005)

Identification of Block Ciphers using Support Vector Machines. - Aroor Dinesh Dileep; Chellu Chandra Sekhar (IJCNN, 2006)

Kernel based Clustering and Vector Quantization for Speech Segmentation. - D. Srikrishna Satish; C. Chandra Sekhar (IJCNN, 2006)

Clustering of Nonlinearly Separable Data Using Spiking Neural Networks. - Lakshmi Narayana Panuku; C. Chandra Sekhar (ICANN (1), 2007)

Spatiostructural Features for Recognition of Online Handwritten Characters in Devanagari and Tamil Scripts. - H. Swethalakshmi; C. Chandra Sekhar; V. Srinivasa Chakravarthy (ICANN (2), 2007)

Kernel Auto-Regressive Model with eXogenous Inputs for Nonlinear Time Series Prediction. - Venkataramana B. Kini; C. Chandra Sekhar (ICCTA, 2007)

Multi-Scale Kernel Latent Variable Models for Nonlinear Time Series Pattern Matching. - Venkataramana B. Kini; C. Chandra Sekhar (ICONIP (2), 2007)

Region-Based Encoding Method Using Multi-dimensional Gaussians for Networks of Spiking Neurons. - Lakshmi Narayana Panuku; C. Chandra Sekhar (ICONIP (1), 2007)

Acoustic Modeling using Vector Quantization in Kernel Feature Space and Classification using String Kernel based Support Vector Machines. - R. Anitha 003; C. Chandra Sekhar (IJCNN, 2007)

Local Density Estimation based Clustering. - Sheetal Reddy Pamudurthy; S. Chandrakala 001; C. Chandra Sekhar (IJCNN, 2007)

Acoustic Modeling Using Continuous Density Hidden Markov Models in the Mercer Kernel Feature Space. - R. Anitha 003; C. Chandra Sekhar (ISNN (1), 2007)

Signal processing based segmentation and hmm based acoustic clustering of syllable segments for low bit rate segment vocoder at 1.4 Kbps. - Sadhana Chevireddy; Hema A. Murthy; C. Chandra Sekhar (EUSIPCO, 2008)

An SVM Based Approach to Cross-Language Adaptation for Indian Languages. - A. Vijaya Rama Raju; C. Chandra Sekhar (ICONIP (2), 2008)

Large margin AR model for time series classification. - Venkataramana B. Kini; C. Chandra Sekhar (ICPR, 2008)

A density based method for multivariate time series clustering in kernel feature space. - S. Chandrakala 001; C. Chandra Sekhar (IJCNN, 2008)

Hyperparameters of Gaussian process as features for trajectory classification. - G. Haranadh; C. Chandra Sekhar (IJCNN, 2008)

Model Based Clustering of Audio Clips Using Gaussian Mixture Models. - S. Chandrakala 001; C. Chandra Sekhar (ICAPR, 2009)

A Graphical Model Based Decoder for Recognition of Loss-concealed VoIP Speech. - Anupam Mandal; K. R. Prasanna Kumar; G. Athithan 001; C. Chandra Sekhar (ICAPR, 2009)

Variational Gaussian Mixture Models for Speech Emotion Recognition. - Harendra Kumar Mishra; C. Chandra Sekhar (ICAPR, 2009)

Ordering and Elimination Based Component Learning Method. - Sheetal Reddy Pamudurthy; C. Chandra Sekhar (ICAPR, 2009)

Combination of generative models and SVM based classifier for speech emotion recognition. - Shanmuganathan Chandrakala; Chellu Chandra Sekhar (IJCNN, 2009)

Representation and feature selection using multiple kernel learning. - Aroor Dinesh Dileep; Chellu Chandra Sekhar (IJCNN, 2009)

Classification of Multi-variate Varying Length Time Series Using Descriptive Statistical Features. - S. Chandrakala 001; C. Chandra Sekhar (PReMI, 2009)

Variational Bayes Adapted GMM Based Models for Audio Clip Classification. - Ved Prakash Sahu; Harendra Kumar Mishra; C. Chandra Sekhar (PReMI, 2009)

Scene Categorization Using Large Margin Gaussian Mixture Models. - T. Veena; Aroor Dinesh Dileep; Chellu Chandra Sekhar (IPCV, 2010)

Classification of varying length multivariate time series using Gaussian mixture models and support vector machines. - S. Chandrakala 001; C. Chandra Sekhar (Int. J. Data Min. Model. Manag., 2010)

Class-Specific Mahalanobis Distance Metric Learning for Biological Image Classification. - B. S. Shajee Mohan; C. Chandra Sekhar (ICIAR (2), 2012)

Speaker recognition using pyramid match kernel based support vector machines. - Aroor Dinesh Dileep; C. Chandra Sekhar (Int. J. Speech Technol., 2012)

HMM based pyramid match kernel for classification of sequential patterns of speech using support vector machines. - Aroor Dinesh Dileep; C. Chandra Sekhar (ICASSP, 2013)

Large margin mixture of AR models for time series classification. - Venkataramana B. Kini; C. Chandra Sekhar (Appl. Soft Comput., 2013)

Bayesian mixture of AR models for time series clustering. - Venkataramana B. Kini; C. Chandra Sekhar (Pattern Anal. Appl., 2013)

HMM Based Intermediate Matching Kernel for Classification of Sequential Patterns of Speech Using Support Vector Machines. - Aroor Dinesh Dileep; C. Chandra Sekhar (IEEE ACM Trans. Audio Speech Lang. Process., 2013)

A Descriptor based on Intensity Binning for Image Matching. - B. Balasanjeevi; C. Chandra Sekhar (ICPRAM, 2014)

Techniques for Improving the Performance of Image Retrieval using Relevance Feedback. - Shrikant Nayak; C. Chandra Sekhar (ICVGIP, 2014)

Concept Level Discriminant Analysis Techniques for Dimension Reduction in Image Classification Tasks. - Ramya K. Raman; C. Chandra Sekhar (ICVGIP, 2014)

Class-specific GMM based intermediate matching kernel for classification of varying length patterns of long duration speech using support vector machines. - Aroor Dinesh Dileep; C. Chandra Sekhar (Speech Commun., 2014)

GMM-Based Intermediate Matching Kernel for Classification of Varying Length Patterns of Long Duration Speech Using Support Vector Machines. - Aroor Dinesh Dileep; Chellu Chandra Sekhar (IEEE Trans. Neural Networks Learn. Syst., 2014)

Example-Specific Density Based Matching Kernels for Scene Classification Using Support Vector Machines. - Abhijeet Sachdev; Veena Thenkanidiyoor; Aroor Dinesh Dileep; C. Chandra Sekhar (ICMLA, 2015)

Automatic Image Annotation Using Convex Deep Learning Models. - Niharjyoti Sarangi; C. Chandra Sekhar (ICPRAM (2), 2015)

Tensor Deep Stacking Networks and Kernel Deep Convex Networks for Annotating Natural Scene Images. - Niharjyoti Sarangi; Chellu Chandra Sekhar (ICPRAM (Selected Papers), 2015)

Two-Pass IB Based Speaker Diarization System Using Meeting-Specific ANN Based Features. - Nauman Dawalatabad; Srikanth R. Madikeri; C. Chandra Sekhar; Hema A. Murthy (INTERSPEECH, 2016)

Distance Metric Learnt Kernel based SVMs for Semi-Supervised Pattern Classification. - B. S. Shajee Mohan; C. Chandra Sekhar (ICAPR, 2017)

Label Correlation Propagation for Semi-supervised Multi-label Learning. - Aritra Ghosh 002; C. Chandra Sekhar (PReMI, 2017)

Kernel Entropy Discriminant Analysis for Dimension Reduction. - Aditya Mehta; C. Chandra Sekhar (PReMI, 2017)

A Two-Stage Conditional Random Field Model Based Framework for Multi-Label Classification. - Abhiram Kumar Singh; C. Chandra Sekhar (PReMI, 2017)

Affinity Propagation Based Closed-Form Semi-supervised Metric Learning Framework. - Ujjal Kr Dutta; C. Chandra Sekhar (ICANN (1), 2018)

Subspace Segmentation Based Metric Learning. - Ujjal Kr Dutta; C. Chandra Sekhar (ICIP, 2018)

Information Bottleneck Based Percussion Instrument Diarization System for Taniavartanam Segments of Carnatic Music Concerts. - Nauman Dawalatabad; Jom Kuriakose; Chellu Chandra Sekhar; Hema A. Murthy (INTERSPEECH, 2018)

Distance metric learning-based kernel gram matrix learning for pattern analysis tasks in kernel feature space. - B. S. Shajee Mohan; C. Chandra Sekhar (Pattern Anal. Appl., 2018)

Incremental Transfer Learning in Two-pass Information Bottleneck Based Speaker Diarization System for Meetings. - Nauman Dawalatabad; Srikanth R. Madikeri; C. Chandra Sekhar; Hema A. Murthy (ICASSP, 2019)

Multi-label Classification Models for Detection of Phonetic Features in building Acoustic Models. - Rupam Ojha; C. Chandra Sekhar (IJCNN, 2019)

A Probabilistic approach for Learning Embeddings without Supervision. - Ujjal Kr Dutta; Mehrtash Harandi; Chellu Chandra Sekhar (CoRR, 2019)

Unsupervised Metric Learning with Synthetic Examples. - Ujjal Kr Dutta; Mehrtash Harandi; C. Chandra Sekhar (AAAI, 2020)

A Geometric Approach for Unsupervised Similarity Learning. - Ujjal Kr Dutta; C. Chandra Sekhar (ICASSP, 2020)

Domain-Specific Semantics Guided Approach to Video Captioning. - Hemalatha Munusamy; C. Chandra Sekhar (WACV, 2020)

Affinity guided Geometric Semi-Supervised Metric Learning. - Ujjal Kr Dutta; Mehrtash Harandi; Chellu Chandra Sekhar (CoRR, 2020)

Unsupervised Deep Metric Learning via Orthogonality Based Probabilistic Loss. - Ujjal Kr Dutta; Mehrtash Harandi; Chellu Chandra Sekhar (IEEE Trans. Artif. Intell., 2020)

Semi-Supervised Metric Learning: A Deep Resurrection. - Ujjal Kr Dutta; Mehrtash Harandi; Chellu Chandra Sekhar (AAAI, 2021)

Front-end Diarization for Percussion Separation in Taniavartanam of Carnatic Music Concerts. - Nauman Dawalatabad; Jilt Sebastian; Jom Kuriakose; C. Chandra Sekhar; Shrikanth Narayanan; Hema A. Murthy (CoRR, 2021)

Unsupervised Domain Adaptation in Speech Recognition using Phonetic Features. - Rupam Ojha; C. Chandra Sekhar (CoRR, 2021)

Novel Architectures for Unsupervised Information Bottleneck Based Speaker Diarization of Meetings. - Nauman Dawalatabad; Srikanth R. Madikeri; C. Chandra Sekhar; Hema A. Murthy (IEEE ACM Trans. Audio Speech Lang. Process., 2021)

Video captioning using Semantically Contextual Generative Adversarial Network. - Hemalatha Munusamy; C. Chandra Sekhar (Comput. Vis. Image Underst., 2022)

Descriptive and Coherent Paragraph Generation for Image Paragraph Captioning Using Vision Transformer and Post-processing. - Naveen Vakada; C. Chandra Sekhar (ACIVS, 2023)

Multi-Modal Hierarchical Attention-Based Dense Video Captioning. - Hemalatha Munusamy; C. Chandra Sekhar (ICIP, 2023)

Memory-efficient Stochastic methods for Memory-based Transformers. - Vishwajit Kumar Vishnu; C. Chandra Sekhar (CoRR, 2023)

Multimodal attention-based transformer for video captioning. - Hemalatha Munusamy; C. Chandra Sekhar (Appl. Intell., 2023)

Leveraging Generated Image Captions for Visual Commonsense Reasoning. - Subham Das; C. Chandra Sekhar (ICIP, 2024)

MetaFix: Semi-supervised Model Agnostic Meta-learning Using Consistency Regularization. - Solarica Palit; C. Chandra Sekhar (ICONIP (3), 2024)

Uncertainty-Guided Metric Learning Without Labels. - Dhanunjaya Varma Devalraju; C. Chandra Sekhar (WACV, 2025)