Titulo Estágio
MOODoke: Music Emotion Recognition via Natural Language Processing
Áreas de especialidade
Sistemas Inteligentes
Engenharia de Software
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
This thesis has two main objectives:
- Technological objective: update the current MOODoke platform, including current Natural Language Processing (NLP) and machine learning tools to perform lyrics-based emotion variation detection (see moodoke.dei.uc.pt)
- Scientific objective: research new NLP methodologies to improve the existing solution
Plano de Trabalhos - Semestre 1
1. Literature review: music and emotion, NLP and machine learning methodologies
2. Integration of NLP and machine learning code into de current software platform
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 and software
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/her 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.
Orientador
Prof. Dr. Rui Pedro Pinto de Carvalho e Paiva
ruipedro@dei.uc.pt 📩