Analysis and Procedural Generation of Musical Content

Code:

MM0063

Acronym:

AGPCM

Keywords
Classification	Keyword
OFICIAL	Music Technology

Instance: 2013/2014 - 2S

Active?	Yes
Responsible unit:	Department of Informatics Engineering
Course/CS Responsible:	Master in Multimedia

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MM	10	Syllabus	1	-	6	56	162

Teaching language

Suitable for English-speaking students

Objectives

- Thorough knowledge of techniques of music information retrieval and automatic generation of music;

- Contact with the relevant literature on music information retrieval and automatic generation of music, including historical generative musical works;

- Knowledge about the potential and the state of the art of music information retrieval and automatic generation of music;

- Implementation of applications with music information retrieval and automatic generation of music.

Learning outcomes and competences

After successfully finishing this class, the student will be able to:

- Know the fields of music information retrieval and automatic music generation, their state of the art and challenges;

- Identify suitable techniques and tools of music information retrieval and automatic music generation for various application;

- Implement software tools and techniques for music information retrieval and automatic music generation.

Working method

Presencial

Program

- Algorithms of rhythmical, timbral and harmonic description;

- Visualization of music data;

- Algorithms of musical similarity and automatic musical recommendations;

- Musical social web;

- Procedural, generative and interactive music;

- Algorithms for rhythmical, harmonic and formal generation;

- Stochastic processes and their use in automatic music generation.

Mandatory literature

Gerhard Nierhaus; Algorithmic composition. ISBN: 978-3-211-99915-8
Eduardo Reck Miranda, John Al Biles (Eds.); Evolutionary Computer Music. ISBN: 1-84628-599-2
Robert Rowe; Machine musicianship. ISBN: 978-0-262-68149-0
Todd Winkler; Composing interactive music. ISBN: 978-0-262-73139-3

Teaching methods and learning activities

- Algorithms of rhythmical, timbral and harmonic description;

- Visualization of music data;

- Algorithms of musical similarity and automatic musical recommendations;

- Musical social web;

- Procedural, generative and interactive music;

- Algorithms for rhythmical, harmonic and formal generation;

 

- Stochastic processes and their use in automatic music generation.

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Participação presencial	60,00
Trabalho laboratorial	40,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	60,00
Frequência das aulas	42,00
Total:	102,00

Calculation formula of final grade

30% - assignments carried out during the semester of music information retrieval;

30% - assignments carried out during the semester of automatic generation of music;

40% - final individual assignment.

 

Classification improvement

Substantial improvement of the final assignment or presentation of another assignment previously approved by the professor.

Observations

Classes will be taught in English if there is foreign students or if it is deemed necessary (e.g. presentations given by foreign professors). Students can either present their assignments in Portuguese or in English.