Vinay Kumar Mittal

According to our database1, Vinay Kumar Mittal authored at least 25 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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PhD thesis 
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Links

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Bibliography

2024
Acoustic Analysis to Characterize Mizo Folk Songs.
Proceedings of the International Conference on Signal Processing and Communications, 2024

Acoustic Characterization of Mizo Folk Songs.
Proceedings of the National Conference on Communications, 2024

2022
Analysis and classification of speech sounds of children with autism spectrum disorder using acoustic features.
Comput. Speech Lang., 2022

2020
Studies on Paralinguistic Sounds, Emotional Speech and Expressive Voices.
Proceedings of the 2020 Workshop on Speech, Music and Mind, 2020

Classifying Speech of ASD Affected and Normal Children Using Acoustic Features.
Proceedings of the 2020 National Conference on Communications, 2020

Discriminating High Arousal and Low Arousal Emotional Speech Using Mahalanobis Distance Among Acoustic Features.
Proceedings of the 2020 National Conference on Communications, 2020

2018
Discriminating between High-Arousal and Low-Arousal Emotional States of Mind using Acoustic Analysis.
Proceedings of the 2018 Workshop on Speech, Music and Mind, 2018

Infant Crying Cause Recognition using Conventional and Deep Learning based Approaches.
Proceedings of the 15th International Conference on Natural Language Processing, 2018

Analyzing Autism Speech of Children in English Vowels Regions by Analysis of Changes in Production Features.
Proceedings of the 15th International Conference on Natural Language Processing, 2018

2017
Component Characterization of Western and Indian Classical Music.
Proceedings of the Advances in Signal Processing and Intelligent Recognition Systems, 2017

Effect of different music genre: Attention vs. meditation.
Proceedings of the Seventh International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, 2017

2016
Changes in shout features in automatically detected vowel regions.
Proceedings of the 2016 International Conference on Signal Processing and Communications (SPCOM), 2016

A sparse representation of the excitation source characteristics of nonnormal speech sounds.
Proceedings of the 10th International Symposium on Chinese Spoken Language Processing, 2016

Significance of automatic detection of vowel regions for automatic shout detection in continuous speech.
Proceedings of the 10th International Symposium on Chinese Spoken Language Processing, 2016

Discriminating features of infant cry acoustic signal for automated detection of cause of crying.
Proceedings of the 10th International Symposium on Chinese Spoken Language Processing, 2016

2015
Analysis of production characteristics of laughter.
Comput. Speech Lang., 2015

A Database of Infant Cry Sounds to Study the Likely Cause of Cry.
Proceedings of the 12th International Conference on Natural Language Processing, 2015

2014
Preliminary analysis of causes of infant cry.
Proceedings of the 2014 IEEE International Symposium on Signal Processing and Information Technology, 2014

An Automatic Shout Detection System Using Speech Production Features.
Proceedings of the Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction, 2014

Study of changes in glottal vibration characteristics during laughter.
Proceedings of the 15th Annual Conference of the International Speech Communication Association, 2014

Significance of aperiodicity in the pitch perception of expressive voices.
Proceedings of the 15th Annual Conference of the International Speech Communication Association, 2014

Naturalistic Audio-Visual Emotion Database.
Proceedings of the 11th International Conference on Natural Language Processing, 2014

2013
Production features for detection of shouted speech.
Proceedings of the 10th IEEE Consumer Communications and Networking Conference, 2013

2012
Effect of Tongue Tip Trilling on the Glottal Excitation Source.
Proceedings of the 13th Annual Conference of the International Speech Communication Association, 2012

A Flexible Analysis Synthesis Tool (FAST) for studying the characteristic features of emotion in speech.
Proceedings of the 2012 IEEE Consumer Communications and Networking Conference (CCNC), 2012


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