Computer Science Applied to Music
A.Y. 2018/2019
Learning objectives
Parte prima (teoria): fornire le basi di codifica ed elaborazione dell'informazione musicale, con particolare riferimento agli ambiti applicativi più rilevanti (internet, basi di dati multimediali, archivi musicali, edizioni musicali, trattamento digitale del suono, programmazione timbrica, composizione musicale e musicologia assistita da elaboratore).
Parte seconda (laboratorio): fornire le basi di sperimentali per l'acquisizione, l'elaborazione e la generazione di informazione musicale, con particolare riferimento agli ambiti applicativi più rilevanti (internet, basi di dati multimediali, archivi musicali, edizioni musicali, programmazione timbrica, trattamento digitale del suono, composizione musicale e musicologia assistita da elaboratore).
Parte seconda (laboratorio): fornire le basi di sperimentali per l'acquisizione, l'elaborazione e la generazione di informazione musicale, con particolare riferimento agli ambiti applicativi più rilevanti (internet, basi di dati multimediali, archivi musicali, edizioni musicali, programmazione timbrica, trattamento digitale del suono, composizione musicale e musicologia assistita da elaboratore).
Expected learning outcomes
Undefined
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Lesson period
Second semester
Prima parte
Course syllabus
Theory:
Formal description of music information. Representation levels. Multilayer description and interaction. Special languages (DARMS, MUSIC V, SMDL, NIFF).
Audio information: linear codes; differential codes; lossless and lossy (MP3 & AAC) codes; audio & music features' recognition within audio signals.
Timbre programming: sampling, mathematical and physical models.
Performing information: the MIDI standard.
Symbolic information: optical music recognition (OMR); music archives; music information querying and retrieval by contents; music electronic publishing; analysis and pattern recognition of scores; generative models.
Structural information: processing and synthesis of symbolic information; Musical Petri Nets.
Multilayer information: MPEG4 SASL/SAOL, MPEG7, MPEG21, IEEE MX.
Technologies for Digital Rights Management.
Formal description of music information. Representation levels. Multilayer description and interaction. Special languages (DARMS, MUSIC V, SMDL, NIFF).
Audio information: linear codes; differential codes; lossless and lossy (MP3 & AAC) codes; audio & music features' recognition within audio signals.
Timbre programming: sampling, mathematical and physical models.
Performing information: the MIDI standard.
Symbolic information: optical music recognition (OMR); music archives; music information querying and retrieval by contents; music electronic publishing; analysis and pattern recognition of scores; generative models.
Structural information: processing and synthesis of symbolic information; Musical Petri Nets.
Multilayer information: MPEG4 SASL/SAOL, MPEG7, MPEG21, IEEE MX.
Technologies for Digital Rights Management.
Seconda parte
Course syllabus
Lab:
Experimental activities in a specially equipped laboratory about:
-digital audio signal processing;
-timbre programming;
-MIDI sequencing.
Experimental activities in a specially equipped laboratory about:
-digital audio signal processing;
-timbre programming;
-MIDI sequencing.
Terza parte
Course syllabus
Lab:
Experimental activities in a specially equipped laboratory about:
-digital score processing;
-analysis/processing/synthesis multilayer models;
-technologies for Digital Rights Managenent.
Experimental activities in a specially equipped laboratory about:
-digital score processing;
-analysis/processing/synthesis multilayer models;
-technologies for Digital Rights Managenent.
Prima parte
INF/01 - INFORMATICS - University credits: 9
Lessons: 72 hours
Professor:
Haus Goffredo Maria
Seconda parte
INF/01 - INFORMATICS - University credits: 3
Lessons: 24 hours
Professor:
Ntalampiras Stavros
Terza parte
INF/01 - INFORMATICS - University credits: 6
Lessons: 48 hours
Professor:
Ludovico Luca Andrea
Professor(s)
Reception:
Tuesday, 10.30 - 12.30 or by appointment
Laboratory of Music Informatics (LIM), Department of Computer Science, 4th floor