V
Vipul Arora
Researcher at Indian Institute of Technology Kanpur
Publications - 47
Citations - 334
Vipul Arora is an academic researcher from Indian Institute of Technology Kanpur. The author has contributed to research in topics: Computer science & Engineering. The author has an hindex of 9, co-authored 30 publications receiving 220 citations. Previous affiliations of Vipul Arora include University of Oxford & Indian Institutes of Technology.
Papers
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Journal ArticleDOI
On-Line Melody Extraction From Polyphonic Audio Using Harmonic Cluster Tracking
Vipul Arora,Laxmidhar Behera +1 more
TL;DR: A novel framework which estimates predominant vocal melody in real-time by tracking various sources with the help of harmonic clusters (combs) and then determining the predominant vocal source by using the harmonic strength of the source.
Journal ArticleDOI
Electroencephalogram Based Reaction Time Prediction With Differential Phase Synchrony Representations Using Co-Operative Multi-Task Deep Neural Networks
TL;DR: In this paper, the authors proposed a method which utilizes the fuzzy common spatial pattern optimized differential phase synchrony representations to inspect electroencephalogram (EEG) synchronization changes from the alert state to the drowsy state.
Journal ArticleDOI
HJB-Equation-Based Optimal Learning Scheme for Neural Networks With Applications in Brain–Computer Interface
TL;DR: Evaluation results substantiate the improvements brought about by the proposed scheme regarding faster convergence and better accuracy, and performance is validated on many small to large scale, synthetic datasets (UCI, LIBSVM datasets).
Journal ArticleDOI
Phonological feature-based speech recognition system for pronunciation training in non-native language learning
TL;DR: The authors implementation of a phonological feature-based ASR system using deep neural networks as an acoustic model and its use for detecting mispronunciation detection, analysing errors, and rendering corrective feedback is presented.
Book ChapterDOI
Analysis of Sanskrit Text: Parsing and Semantic Relations
TL;DR: The proposed Sanskrit parser is able to create semantic nets for many classes of Sanskrit paragraphs and is taking care of both external and internal sandhi in the Sanskrit words.