Search Results for author: Vinoo Alluri

Found 8 papers, 1 papers with code

Tollywood Emotions: Annotation of Valence-Arousal in Telugu Song Lyrics

no code implementations16 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.

Emotion Recognition Music Emotion Recognition +1

Sonus Texere! Automated Dense Soundtrack Construction for Books using Movie Adaptations

no code implementations2 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.

How Much do Lyrics Matter? Analysing Lyrical Simplicity Preferences for Individuals At Risk of Depression

no code implementations15 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.

Transformer-based approach towards music emotion recognition from lyrics

1 code implementation6 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.

Emotion Recognition Information Retrieval +5

Static and Dynamic Measures of Active Music Listening as Indicators of Depression Risk

no code implementations28 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.

Tag2Risk: Harnessing Social Music Tags for Characterizing Depression Risk

no code implementations26 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.

valid

Towards Multimodal MIR: Predicting individual differences from music-induced movement

no code implementations21 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.

Information Retrieval Music Information Retrieval +1

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