This book features original papers from 27th International Symposium on Frontiers of Research in Speech and Music (FRSM 2023), jointly organized by Sardar Vallabhbhai National Institute of Technology, Surat, India, and Sir C.V. Raman Centre for Physics and Music, Jadavpur University, Kolkata, India, during 4–5 August 2023. The book is organized into four main sections, considering both technological advancement and interdisciplinary nature of speech, music, language and their applications. The first section includes chapters related to computational, modelling and cognitive aspects of the speech signal. The second part contains chapters covering the foundations of both vocal and instrumental music processing with the signal, computational and cognitive aspects. The third section relates to the variety of research being done in the peripheral areas of languages and linguistics with special focus on regional languages of India. A lot of research is being performed within the speech and music information retrieval domain which is potentially interesting for most users of computers and the Internet. Therefore, the fourth and final section is dedicated to the chapters related to multidisciplinary applications of speech and music signal processing.
Framework for Detecting Toxic speech using BERT and Deep Learning.- Speech Emotion Classification Using Deep Learning.- ML Based Application for Enhanced Communication With Specially Abled Children.- Acoustic Phonetic Analysis of Vowels of Native Bengali Speakers with Parkinson’s Disease.- Recent Advancement in Accent Conversion using Deep Learning Techniques: A comprehensive review .- Speech Enhancement: Traditional and Deep Learning Techniques.- Continuing CompMusic: New approaches in the computational analysis of Carnatic Music.- An Ethnomusicological study of Darpawngi’s Mizo folksongs: A Cantometric Experiment.- An approach of similarity measure in Hindustani music.- Ornamentation in Hindustani vocal music.- A comparative Study of the non-nasal and nasal voice in Hindustani vocal music.- Regression Approach for Shruthi Identification from Indian Classical Instrumental Polyphonic Audio.- Music-Evoked Emotion Classification from EEG: An Image Based CNN Approach.- Perception of Devotion and Happiness in Indian Spiritual Music: An Acoustical and Audience Response Exploration.- Identifying Correlations Between Hindustani Music And The Brain: A Nonlinear EEG based exploration.- Representation and Analysis of Dynamics for Automatic Music Assessment in Hindustani Vocal Music.- Emotion and Instrument audio classification of Indian Classical Music recordings using transformers.- Styles and Rhythms of musical transitions in Indian Ragas: An Acoustical Exploration.- A statistical approach to the acoustical analysis of harmonics and timbre of tabla strokes.
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