Back close
Admissions
S-Lalitha_asst-professor_ece_bengaluru_campus

Dr. S. Lalitha

Assistant Professor (SG), Department of Electronics and Communication, School of Engineering, Bengaluru

Qualification: M.Tech, Ph.D
s_lalitha@blr.amrita.edu
Research Interest: Speech and Audio Signal processing, Music Signal Processing, Machine Learning, Natural Language Processing, Image Processing, Artificial Intelligence

Bio Publications Professional Appointments Major Research Interests Courses Taught Student Guidance
Bio

Dr. S. Lalitha currently serves as Assistant Professor (SG) at the Department of Electronics and Communication, Amrita School of Engineering, Bengaluru Campus.

Education

  • Ph.D.
    From: Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Bengaluru, Karnataka
  • M. Tech. in Digital Communication (2008)
    From: M S Ramiah Institute of Technology Bengaluru, VTU, Karnataka,
  • B.E. in Electronics and Communication Engineering (1998)
    From: Vijayanagar Engineering College, Bellary, Gulbarga University, Karnataka.

Area of Specialization

Speech and audio signal processing, Machine Learning

Courses taught at Diploma/ Post Diploma/ Under Graduate/ Post Graduate/ Post Graduate Diploma Level

Signals and Systems, Digital Signal Processing, Speech and Audio Signal Processing, Control Systems Engineering, Digital Communication, Machine Learning

Total Work Experience 19 years
Teaching 19 years
Research Publications (No.of papers published in National/International Journals/Conferences) 27

 

Publications

Journal Article

Year : 2023

Dementia Speech Dataset Creation and Analysis in Indic Languages—A Pilot Study

Cite this Research Publication : Susmitha Vekkot, Nagulapati Naga Venkata Sai Prakash, Thirupati Sai Eswar Reddy, Satwik Reddy Sripathi, S. Lalitha, Deepa Gupta, Mohammed Zakariah, and Yousef Ajami Alotaibi published a paper titled, “Dementia Speech Dataset Creation and Analysis in Indic Languages—A Pilot Study”, in IEEE Access with Impact Factor 3.9 on 20th November 2023

Publisher : IEEE

Year : 2022

Dementia detection from speech using machine learning and deep learning architectures

Cite this Research Publication : Kumar, M. R., Vekkot, S., Lalitha, S., Gupta, D., Govindraj, V. J., Shaukat, K., ... &Zakariah, M. (2022). Dementia detection from speech using machine learning and deep learning architectures. Sensors, 22(23), 9311

Publisher : Sensors

Year : 2021

Investigation of automatic mixed-lingual affective state recognition system for diverse Indian languages

Cite this Research Publication : Lalitha, S., & Gupta, D. (2021). Investigation of automatic mixed-lingual affective state recognition system for diverse Indian languages. Journal of Intelligent & Fuzzy Systems, (Preprint), 1-10.

Publisher : Journal of Intelligent & Fuzzy Systems

Year : 2021

Face recognition and tracking for security surveillance

Cite this Research Publication : Nair, S. P., Abhinav Reddy, K., Alluri, P. K., & Lalitha, S. (2021). Face recognition and tracking for security surveillance. Journal of Intelligent & Fuzzy Systems, (Preprint), 1-9.

Publisher : Journal of Intelligent & Fuzzy Systems

Year : 2021

Mental Illness Disorder Diagnosis Using Emotion Variation Detection from Continuous English Speech

Cite this Research Publication : Lalitha, S., Gupta, D., Zakariah, M., & Alotaibi, Y. A. (2021). Mental Illness Disorder Diagnosis Using Emotion Variation Detection from Continuous English Speech. CMC-COMPUTERS MATERIALS & CONTINUA, 69(3), 3217-3238.

Publisher : CMC-COMPUTERS MATERIALS & CONTINUA

Year : 2020

Investigation of multilingual and mixed-lingual emotion recognition using enhanced cues with data augmentation

Cite this Research Publication : S. Lalitha, Dr. Deepa Gupta, Zakariah, M., and Alotaibi, Y. Ajami, “Investigation of multilingual and mixed-lingual emotion recognition using enhanced cues with data augmentation”, Applied Acoustics, vol. 170, p. 107519, 2020.

Publisher : Applied Acoustics,

Year : 2020

A vital neurodegenerative disorder detection using speech cues

Cite this Research Publication : B. Jahnavi, Supraja, B., and Lalitha, S., “A vital neurodegenerative disorder detection using speech cues”, Journal of Intelligent & Fuzzy Systems, vol. 38, pp. 1-9, 2020.

Publisher : Journal of Intelligent & Fuzzy Systems,

Year : 2019

Affective state recognition using audio cues

Cite this Research Publication : M. P. Krishna, R. Reddy, P., Narayanan, V., Lalitha, S., and Gupta, D., “Affective state recognition using audio cues”, Journal of Intelligent and Fuzzy Systems, vol. 36, pp. 2147-2154, 2019.

Publisher : Journal of Intelligent and Fuzzy Systems, IOS Press

Year : 2018

Enhanced speech emotion detection using deep neural networks

Cite this Research Publication : S. Lalitha, Tripathi, S., and Gupta, D., “Enhanced speech emotion detection using deep neural networks”, International Journal of Speech Technology, 2018.

Publisher : International Journal of Speech Technology

Year : 2018

An epitomization of stress recognition from speech signal

Cite this Research Publication : V. Narayanan, Lalitha, S., and Gupta, D., “An epitomization of stress recognition from speech signal”, International Journal of Engineering and Technology(UAE), vol. 7, pp. 61-68, 2018.

Publisher : International Journal of Engineering and Technology(UAE)

Year : 2015

Emotion Detection Using MFCC and Cepstrum Features

Cite this Research Publication : Sreeram, Lalitha & Geyasruti, D. & Narayanan, Ramachandran & M, Shravani. (2015). Emotion Detection Using MFCC and Cepstrum Features. Procedia Computer Science, vol. 70. pp-29-35.

Conference Paper

Year : 2022

Comparative study of Deep Classifiers for Early Dementia Detection using Speech Transcripts

Cite this Research Publication : Nambiar, A. S., Likhita, K., Pujya, K. S., Gupta, D., Vekkot, S., &Lalitha, S. (2022, November). Comparative study of Deep Classifiers for Early Dementia Detection using Speech Transcripts. In 2022 IEEE 19th India Council International Conference (INDICON) (pp. 1-6). IEEE.

Publisher : IEEE

Year : 2021

Sentiment and Emotion Analysis for Effective Human-Machine Interaction during Covid-19 Pandemic

Cite this Research Publication : Prasad, G., Dikshit, A., & Lalitha, S. (2021, August). Sentiment and Emotion Analysis for Effective Human-Machine Interaction during Covid-19 Pandemic. In 2021 8th International Conference on Signal Processing and Integrated Networks (SPIN) (pp. 909-915) IEEE

Publisher : IEEE

Year : 2018

Personality Identification Using Auditory Nerve Modelling of Human Speech

Cite this Research Publication : K. Gokul and Lalitha, S., “Personality Identification Using Auditory Nerve Modelling of Human Speech”, in 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Bangalore, 2018.

Publisher : 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

Year : 2018

Affective State Recognition using Image Cues

Cite this Research Publication : P. R Reddy, P Krishna, M., Narayanan, V., and Lalitha, S., “Affective State Recognition using Image Cues”, in 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Bangalore, India, 2018.

Publisher : 2018 International Conference on Advances in Computing, Communications and Informatics

Year : 2018

An Encapsulation of Vital Non-Linear Frequency Features for Various Speech Applications

Cite this Research Publication : S. Lalitha and Dr. Deepa Gupta, “An Encapsulation of Vital Non-Linear Frequency Features for Speech Applications”, in International Conference on Intelligent Computing (ICIC) 2018, Amrita School of Engineering, Bengaluru, 2018.

Publisher : International Conference on Intelligent Computing (ICIC) 2018, Amrita School of Engineering,

Year : 2018

An Encapsulation of Vital Non-Linear Frequency Features for Speech Applications

Cite this Research Publication : S. Lalitha and Dr. Deepa Gupta, “An Encapsulation of Vital Non-Linear Frequency Features for Speech Applications”, in International Conference on Intelligent Computing (ICIC) 2018, Amrita School of Engineering, Bengaluru, 2018.

Publisher : International Conference on Intelligent Computing (ICIC) 2018

Year : 2018

Stress Recognition Using Auditory Features for Psychotherapy in Indian Context

Cite this Research Publication : V. Narayanan, Lalitha, S., and Gupta, D., “Stress Recognition Using Auditory Features for Psychotherapy in Indian Context”, in Proceedings of the 2018 IEEE International Conference on Communication and Signal Processing, ICCSP 2018, 2018, pp. 426-432.

Publisher : Proceedings of the 2018 IEEE International Conference on Communication and Signal Processing, ICCSP 2018

Year : 2018

Personality Traits from Speech Signal Using Cross-Corpus Technique

Cite this Research Publication : N. Vijay, Tripathi, S., and Lalitha, S., “Personality Traits from Speech Signal Using Cross-Corpus Technique”, in 2017 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017, 2018.

Publisher : 2017 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017

Year : 2018

Affective state recognition using audio cues

Cite this Research Publication : M. P Krishna, R Reddy, P., Narayanan, V., Lalitha, S., and Dr. Deepa Gupta, “Affective state recognition using audio cues”, in International Symposium on Intelligent Systems Technologies and Applications (ISTA 2018), PES Institute of Technology, Bengaluru, South Campus, India, 2018.

Publisher : International Symposium on Intelligent Systems Technologies and Applications (ISTA 2018)

Year : 2017

Stress Recognition Using Sparse Representation of Speech Signal for Deception Detection Applications in Indian Context

Cite this Research Publication : K. T. K. Aswath Varsha and Lalitha, S., “Stress Recognition Using Sparse Representation of Speech Signal for Deception Detection Applications in Indian Context”, in 2017 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), Coimbatore, India, 2017.

Publisher : 2017 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC),

Year : 2017

Affective computing using speech processing for call centre applications

Cite this Research Publication : R. K. Gowda, Nimbalker, V., Lavanya, R., Lalitha, S., and Tripathi, S., “Affective computing using speech processing for call centre applications”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017.

Year : 2016

Emotion detection using perceptual based speech features

Cite this Research Publication : S. Lalitha and Dr. Shikha Tripathi, “Emotion detection using perceptual based speech features”, in India Conference (INDICON), 2016 IEEE Annual, 2016.

Publisher : India Conference (INDICON), 2016 IEEE Annual, IEEE.

Year : 2015

Time-frequency and phase derived features for emotion classification

Cite this Research Publication : S. Lalitha, Chaitanya, K. K., Teja, G. V. N., Varma, K. V., and Dr. Shikha Tripathi, “Time-frequency and phase derived features for emotion classification”, in 12th IEEE International Conference Electronics, Energy, Environment, Communication, Computer, Control: (E3-C3), INDICON 2015, 2015.

Publisher : 12th IEEE International Conference Electronics, Energy, Environment, Communication, Computer, Control: (E3-C3), INDICON 2015

Year : 2015

Speech emotion recognition using DWT

Cite this Research Publication : S. Lalitha, Mudupu, A., Nandyala, B. V., and Munagala, R., “Speech emotion recognition using DWT”, in 2015 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2015, 2015.

Publisher : 2015 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2015

Year : 2014

Emotion Recognition through Speech Signal for Human-Computer Interaction

Cite this Research Publication : S. Lalitha, S., P., T.H., A., V., M., and S., T., “Emotion Recognition through Speech Signal for Human-Computer Interaction”, in Proceedings - 2014 5th International Symposium on Electronic System Design, ISED 2014, 2014, pp. 217-218.

Publisher : Proceedings - 2014 5th International Symposium on Electronic System Design, ISED 2014

Conference Proceedings

Year : 2020

An End-to-End Model for Detection and Assessment of Depression Levels using Speech

Cite this Research Publication : N. S. Srimadhur and Lalitha, S., “An End-to-End Model for Detection and Assessment of Depression Levels using Speech”, Procedia Computer Science, vol. 171. pp. 12-21, 2020.

Publisher : Procedia Computer Science

Year : 2014

Speech emotion recognition

Cite this Research Publication : S. Lalitha, Madhavan, A., Bhushan, B., and Saketh, S., “Speech emotion recognition”, International Conference on Advances in Electronics Computers and Communications. pp. 1-4, 2014.

Publisher : International Conference on Advances in Electronics Computers and Communications

Book Chapter

Year : 2021

Automatic Detection of Parkinson Speech Under Noisy Environment

Cite this Research Publication : Jayashree, R. J., Ganesh, S., Karanth, S. C., & Lalitha, S. (2021). Automatic Detection of Parkinson Speech Under Noisy Environment. In Advances in Computing and Network Communications (pp. 179-191). Springer, Singapore.

Publisher : Springer, Singapore

Year : 2020

A Chronic Psychiatric Disorder Detection Using Ensemble Classification

Cite this Research Publication : V. J. Jithin, G. Reddy, M., Anand, R., and Lalitha, S., “A Chronic Psychiatric Disorder Detection Using Ensemble Classification”, in Advances in Signal Processing and Intelligent Recognition Systems, S. M. Thampi, Hegde, R. M., Krishnan, S., Mukhopadhyay, J., Chaudhary, V., Marques, O., Piramuthu, S., and Corchado, J. M., Eds. Singapore: Springer Singapore, 2020.

Publisher : Advances in Signal Processing and Intelligent Recognition Systems

Professional Appointments
Year Affiliation
2008 to Till date Amrita School of Engineering, Bengaluru, Karnataka
2000-2004 Vijayanagar Engineering College, Bellary, Karnataka
Major Research Interests
  • Speech and Audio Signal processing
  • Music Signal Processing
  • Machine Learning
  • Artificial Intelligence
Courses Taught
  • Speech and Audio Signal Processing
  • Signals and Systems
  • Digital Signal Processing
  • Control Systems
  • Electric Circuits
  • Electronics Engineering
  • Computer Organization and Architecture
  • Fundamentals of Machine learning
Student Guidance

Undergraduate students

Sl. No. Name of the Student(s) Topic Status – Ongoing/Completed Year of Completion
1 J Jatin, kalaga Pranav, PudappaKoushik Reddy Continous speech emotion recognition Ongoing
2 HritwikJoardar, SauhardSoni, Sparshkapoor Mixed lingual speech digit recognition for north indian languages Ongoing
3 BolledduSannidhi, A.V.B.Vamsi Stuttered speech analysis Ongoing
4 Lakshmi Sudha CharithaKongala Sowmya  Language Diarization System For Bilingual Code-Switched Indian Speech Completed 2023
5 NagavelliRachana MaddineniJotshna  Multilingual and mixed-lingual digit speech recognition system for the Indian context Completed 2023
6 DevarashettyDeekshita N. Sridevi Diverse Mixed-lingual Speech Emotion Recogntion Completed 2023
7 V.Nanda Kishore, R Mega Sai, V Avinash Speech Assistive Device For Visually Impaired People Using Raspberry Pi Completed 2022
8 M.V.Sathvik, K.M.V.M.Varma Detection Of Parkinson’s Disease Using Speech Signals Completed 2022
9 AdaviVarshita, VaishnaviVarma ,C.K AkshithaKamshetty  SPEECH TO SIGN LANGUAGE INTERPRETER Completed 2022
10 Rupesh Kumar Investigation And Detection Of Dementia (Alzheimer Type) From Speech Samples Using Deep Learning Architectures Ongoing Will be completed by April 2021
11 Srivatsa, Rushendra, Leela Nagendra Speech emotion recognition in Noisy Background Ongoing Will be completed by April 2021
12 Karthik, Suresh Design and Implementation of Early driver drowsiness detection using EEG signals Ongoing Will be completed by April 2021
13 Sreelu, Abhinov reddy, Prithvi Krisshna Face Recognition And Tracking For Security Surveillance Completed 2020
14 Rohit, Surya Pavan teja, Naga Sai Sri Tejaswi Colour Image Segmentation of Fundus Blood Vessels for the Detection of Hypertensive

Retinopathy

 Completed 2020
15 Janani, Sanjana, Sneha DETECTION OF PARKINSON’S DISEASE USING MACHINE LEARNING ALGORITHM UNDER NOISY CONDITION Completed 2020
16 Jahnavi, B. & Supraja A vital neurodegenerative disorder detection using speech cues Completed 2019
17 Manoj, Jithin, Anand A Chronic Psychiatric Disorder Detection Using
Ensemble Classication		 Completed 2019
18 Murali, Pradeep Emotion Recognition using Image Cues Completed 2018
19 Rakshith, Lavanya, Vandana Affective Computing for call centre applications Completed 2017
20 Prem Reddy, Sudheer, Durga Prasad Stress and emotion recognition using speech Completed 2016

Postgraduate students

Sl. No. Name of the Student(s) Topic Status – Ongoing/Completed Year of Completion
1 Madhur An End-to-End Model for Detection and Assessment of Depression Levels using Speech Completed 2019
2 Veena Narayan Emotion and stress analysis using speech Completed 2018
3 Gokul Speech based Stress recognition Completed 2018
4 Nekha vijay Personality Traits from Speech Signal Using Cross-Corpus Technique Completed 2017
5 Aswathi Varsha Stress Recognition Using Sparse Representation of Speech Signal for Deception Detection Applications in Indian Context Completed 2017
Admissions Apply Now