no code implementations • 16 Mar 2023 • R Guru Ravi Shanker, B Manikanta Gupta, BV Koushik, Vinoo Alluri
Fine-tuned XLMRoBERTa performs better than the SVM by improving macro-averaged F1-scores of 54. 69%, 67. 61%, 34. 13% to 77. 90%, 80. 71% and 58. 33% for valence, arousal and quadrant classifications, respectively, on 10-fold cross-validation.
no code implementations • 2 Dec 2022 • Jaidev Shriram, Makarand Tapaswi, Vinoo Alluri
Reading, much like music listening, is an immersive experience that transports readers while taking them on an emotional journey.
no code implementations • 15 Sep 2021 • Jaidev Shriram, Sreeharsha Paruchuri, Vinoo Alluri
In the current study, we examine lyrical simplicity, measured as the Compressibility and Absolute Information Content of the text, associated with preferences of individuals at risk for depression.
1 code implementation • 6 Jan 2021 • Yudhik Agrawal, Ramaguru Guru Ravi Shanker, Vinoo Alluri
The task of identifying emotions from a given music track has been an active pursuit in the Music Information Retrieval (MIR) community for years.
no code implementations • 28 Sep 2020 • Aayush Surana, Yash Goyal, Vinoo Alluri
Music, an integral part of our lives, which is not only a source of entertainment but plays an important role in mental well-being by impacting moods, emotions and other affective states.
no code implementations • 26 Jul 2020 • Aayush Surana, Yash Goyal, Manish Shrivastava, Suvi Saarikallio, Vinoo Alluri
Studies have shown musical engagement to be an indirect representation of internal states including internalized symptomatology and depression.
no code implementations • 21 Jul 2020 • Yudhik Agrawal, Samyak Jain, Emily Carlson, Petri Toiviainen, Vinoo Alluri
As the field of Music Information Retrieval grows, it is important to take into consideration the multi-modality of music and how aspects of musical engagement such as movement and gesture might be taken into account.
no code implementations • 6 Jun 2013 • Tuomo Sipola, Feng-Yu Cong, Tapani Ristaniemi, Vinoo Alluri, Petri Toiviainen, Elvira Brattico, Asoke K. Nandi
In this research, we used the recently developed diffusion map for dimensionality reduction in conjunction with spectral clustering.