Titlebook: Advances in Speech and Music Technology; Proceedings of FRSM Anupam Biswas,Emile Wennekes,Alicja Wieczorkowska Conference proceedings 2021

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Conference proceedings 2021ational Institute of Technology, Silchar, India, during 8–9 October 2020. The book is organized in five sections, considering both technological advancement and interdisciplinary nature of speech and music processing. The first section contains chapters covering the foundations of both vocal and ins

ITCH

Mehdi Achour,Jamel Belhadj Tahernd the singer’s formant were extracted and compared statistically. Results of the study revealed a higher singing power ratio for the pre-fatigue condition compared to the post-fatigue condition and the singer’s formant did not show significant differences between the pre-fatigue and post-fatigue co

GUMP

Sangman Moh,Kyoung Park,Sungnam Kiman classical music which are fundamental in unfolding the musical ornamentation of a raga. Here, we have discussed only two ornamentations, viz. meend and andolan. The study leads to identifying the style of vocal performers.

Oscillate

SCTP Based Framework for Mobile Web Agent and amplitude of the speech signals. Depending on these parameters, the speech signals are classified into appropriate classes of emotions through various algorithms of pattern recognition and machine learning. An algorithm for emotion detection is proposed here and is implemented in R tool. The al

mortuary

Computer and Information Sciences IIs to identify the gender of the speaker by using highly accurate, efficient, and reliable machine learning algorithms. These two are the most important aspects of any audio surveillance system. The algorithm is tested on the Open Speech and Language Resources (Open SLR) dataset. This dataset consist

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Ata Turk,B. Barla Cambazoglu,Cevdet Aykanatis presented for this task which distinguishes the five major types of folk songs of Bengal. Experiments were performed with over 43 K clips, and the best correct classification rate of 99.73% was obtained with LPCC-based features considering extremely short length clips.

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