Automatic mood detection and tracking of music audio signals
By Lie Lu, Dan Liu, HongJiang Zhang. IEEE Transactions on Audio, Speech, and Language Processing, 2006
584 citations recorded by the source corpus.
Subfields: Cognitive Neuroscience, Signal Processing
View Paper: https://www.semanticscholar.org/paper/9d4a2052502fe2c60e48d7c8997da1269df6f48f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cognitive Neuroscience
- Mohammad Soleymani
- Thierry Pun
- Christian Mühl
- Anton Nijholt
- Masataka Goto
- Marc Leman
- Guojun Lu
- Dengsheng Zhang
In Signal Processing
- Malcolm Slaney
- Marc Leman
- Michael A. Casey
- Remco C. Veltkamp
- Christophe Rhodes
- Masataka Goto
- Douglas R. Turnbull
- Mohammad Soleymani
Citations in the corpus
- Multi-Label Classification of Music into Emotions (2008, methodology): “The four main emotion classes of Thayer’s model were used as the emotion model in [9].”
- A Survey of Audio-Based Music Classification and Annotation (2011, methodology): “classification, a large amount of works used rhythm features [21], [22], [25], [27].”
- State of the Art Report: Music Emotion Recognition: A State of the Art Review (2010, methodology): “Other recent approaches have adopted a generalized approach to feature extraction, compiling multiple feature sets (resulting in high dimensional spaces) and employing dimensionality reduction techniques [50,59].”
- MoodScope: building a mood sensor from smartphone usage patterns (2013, unknown): “We#TAB##R# implement#TAB##R# the#TAB##R# application#TAB##R# by#TAB##R# manually#TAB##R# tagging#TAB##R# the songs#TAB##R# with#TAB##R# matching#TAB##R# mood#TAB##R# states,#TAB##R# but#TAB##R# automatically#TAB##R# tagging#TAB##R# is#TAB##R# also#TAB##R# feasible#TAB##R# [23].”
- DEAP: A Database for Emotion Analysis ;Using Physiological Signals (2012, background): “There are also various studies on music affective characterization from acoustic features [32], [33], [34].”
- Content-Based Music Information Retrieval: Current Directions and Future Challenges (2008, methodology): “Recent approaches in MIR and in music cognition have studied the relationship between low-level perceptual/acoustic features and semantic emotional/affective concepts such as mood [ 124 ], [128]; this is a promising new direction for the field.”
- Are the Emotions Expressed in Music Genre-specific? An Audio-based Evaluation of Datasets Spanning Classical, Film, Pop and Mixed Genres (2011, background): “Whereas modelling emotion categories has been a common choice among the MIR community (e.g. Lu et al., 2006; Skowronek et al., 2007; Yang et al., 2007), the underlying emotions are perhaps captured in a more subtle and realistic way by modelling them in terms of continua within and between the…”