Data Acquisition For Music Processing 3 ENG3016
- Academic Session: 2023-24
- School: School of Engineering
- Credits: 20
- Level: Level 3 (SCQF level 9)
- Typically Offered: Runs Throughout Semesters 1 and 2
- Available to Visiting Students: Yes
Short Description
This course presents techniques from engineering and computing science which are applicable in the empirical study of musical data (sound, score, structure and performance) with examples from a selection of appropriate musical works presented in different formats. Students will compare how musical information is acquired from different sources, including scores, performances, recordings and music-theoretical texts.
Timetable
Weekly lectures and five staged tutorial exercises.
Requirements of Entry
None.
Excluded Courses
None.
Co-requisites
None.
Assessment
20% Laboratory (haptic data capture and extraction from audio and video recordings),
20% Tutorials (transcription and mark-up exercises),
30% Written
30% Oral (assessment of musical analysis and markup skills) Examination
Main Assessment In: April/May
Course Aims
The aims of this course are to:
• equip candidates with the knowledge and skills to draw out information about musical processes, including those of composition, performance and analysis, from a variety of different sources;
• present the different characters and purposes of diverse representations of music;
• apply modern engineering techniques of measurement to acquire, store and analyse performance data.
Intended Learning Outcomes of Course
By the end of this course students will be able to:
■ recall the basic terminology required for the analysis of musical data;
■ list common formal musical archetypes;
■ state the classical texts in data acquisition and music processing and summarise their main contributions to the field;
■ transcribe recorded material into score form;
■ employ modern analysis techniques (including note boundary location and pitch determination) to recorded material;
■ identify and classify melodic, harmonic, rhythmic and gestural material rigorously, and in a way commensurate with requirements of computer representation;
■ judge optimal techniques for storage of music data for subsequent analysis (including in SQL databases);
■ represent music in XML, Music-XML and PLM formats, and parse such representations (with, for example Regular Expressions and YACC Grammars);
■ analyse and markup selected musical examples from all periods of the history of Western music;
■ explain the relevance and importance of performance gestures to music;
■ list typical acquisition techniques for gestural capture, including those associated with audio ("indirect") gestural capture and video/haptic ("direct") gestural capture;
■ select appropriate sensors for gestural capture;
■ design appropriate gestural capture systems for subsequent performance analysis;
■ assess the advantages and disadvantages of discrete event file formats (e.g. MIDI, Open Sound Control);
■ evaluate algorithms for the audio and video acquisition of performance parameters.
Minimum Requirement for Award of Credits
Students must attend the degree examination and submit at least 75% by weight of the other components of the course's summative assessment.
Students must attend the timetabled laboratory classes.
Note that these are minimum requirements: good students will achieve far higher participation/submission rates. Any student who misses an assessment or a significant number of classes because of illness or other good cause should report this by completing a MyCampus absence report.