34 citations · 48 across the 10 of their papers we have counts for
11 papers
Muse-it: A Tool for Analyzing Music Discourse on Reddit
Jatin Agarwala, George Paul, Nemani Harsha Vardhan +1
Music engagement spans diverse interactions with music, from selection and emotional response to its impact on behavior, identity, and social connections. Social media platforms pr…
Lyrically Speaking: Exploring the Link Between Lyrical Emotions, Themes and Depression Risk
Pavani Chowdary, Bhavyajeet Singh, Rajat Agarwal +1
Lyrics play a crucial role in affecting and reinforcing emotional states by providing meaning and emotional connotations that interact with the acoustic properties of the music. Sp…
Tollywood Emotions: Annotation of Valence-Arousal in Telugu Song Lyrics
R Guru Ravi Shanker, B Manikanta Gupta, BV Koushik +1
Emotion recognition from a given music track has heavily relied on acoustic features, social tags, and metadata but is seldom focused on lyrics. There are no datasets of Indian lan…
Sonus Texere! Automated Dense Soundtrack Construction for Books using Movie Adaptations
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. Listening to complementary music has the potential…
Multimodal Fusion Based Attentive Networks for Sequential Music Recommendation
Kunal Vaswani, Yudhik Agrawal, Vinoo Alluri
Music has the power to evoke intense emotional experiences and regulate the mood of an individual. With the advent of online streaming services, research in music recommendation se…
How Much do Lyrics Matter? Analysing Lyrical Simplicity Preferences for Individuals At Risk of Depression
Jaidev Shriram, Sreeharsha Paruchuri, Vinoo Alluri
Music affects and in some cases reflects one's emotional state. Key to this influence is lyrics and their meaning in conjunction with the acoustic properties of the track. Recent w…
Transformer-based approach towards music emotion recognition from lyrics
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. Music emotion recognition has typ…
Static and Dynamic Measures of Active Music Listening as Indicators of Depression Risk
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…
Tag2Risk: Harnessing Social Music Tags for Characterizing Depression Risk
Aayush Surana, Yash Goyal, Manish Shrivastava +2
Musical preferences have been considered a mirror of the self. In this age of Big Data, online music streaming services allow us to capture ecologically valid music listening behav…
Towards Multimodal MIR: Predicting individual differences from music-induced movement
Yudhik Agrawal, Samyak Jain, Emily Carlson +2
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…
Diffusion map for clustering fMRI spatial maps extracted by independent component analysis
Tuomo Sipola, Fengyu Cong, Tapani Ristaniemi +4
Functional magnetic resonance imaging (fMRI) produces data about activity inside the brain, from which spatial maps can be extracted by independent component analysis (ICA). In dat…