Titulo Estágio
Automatic Music Emotion Recognition
Áreas de especialidade
Sistemas Inteligentes
Local do Estágio
DEI
Enquadramento
Music emotion-based classification is a research area of increasing interest in Music Information Retrieval (MIR). It has a wide range of applications in fields such us automatic music classification, playlist generation and similarity analysis.
In fact, recent studies identify music emotion as an important criterion used by people in music retrieval and organization. Moreover, music psychology and education acknowledge the emotion component of music as the one most strongly associated with music expressivity.
Objetivo
The main objective of this thesis is to analyze music in terms of emotion content information, e.g., happiness, tension, melancholy, contentment, etc. This involves the study and derivation of emotion-like features, development of emotion-based machine learning classifiers and emotion-based similarity metrics.
The analysis is to be carried out in the audio signal and/or the lyrics of the songs. Furthermore, textual information from social networks such as last.fm and twitter might be employed.
Plano de Trabalhos - Semestre 1
1. Literature review: music and emotion, feature extraction and machine learning methodologies
2. Dataset acquisition and/or improvement of current one
3. Formulation of research questions
4. Formulation of hypotheses to answer the research questions
Plano de Trabalhos - Semestre 2
5. Development and evaluation of the proposed algorithms
6. Thesis writing
7. Possible writing of a scientific research paper
Condições
The MSc candidate will join an active research group, which will give him strong scientific support, in an excellent work atmosphere.
Moreover, the candidate will have the opportunity to work in a cutting-edge research area with several open and exciting research possibilities, with plenty of room for scientific innovation.
Observações
References:
- Juslin P.N., Karlsson J., Lindström E., Friberg A. and Schoonderwaldt E. (2006) “Play It Again With Feeling: Computer Feedback in Musical Communication of Emotions”, Journal of Experimental Psychology: Applied, Vol. 12, No.2, pp. 79-95.
- Lu, Liu and Zhang (2006), “Automatic Mood Detection and Tracking of Music Audio Signals”, IEEE Transaction on Audio, Speech and Language Processing, Vol. 14, No. 1, pp. 5-18.
Orientador
Prof. Dr. Rui Pedro Pinto de Carvalho e Paiva
ruipedro@dei.uc.pt 📩