Towards Computer-Assisted Transcription and Description of Music Recordings
Automatic transcription, i.e. computing a symbolic musical representation from a music recording, is one of the main research challenges in the field of sound and music computing. For monophonic music material the obtained transcription is a single musical line, usually a melody, and in polyphonic there is an interest in transcribing the predominant melodic line. In addition to transcribing, current technologies are able to extract other musical descriptions related to tonality, rhythm or instrumentation from music recordings. Automatic description could potentially complement traditional methodologies for music analysis.In this talk I will first present the state-of-the art on automatic transcription and description of music audio signals. I will illustrate it with our own research on tonality estimation, melodic transcription and rhythmic characterization. I will show that, although current research is promising, current algorithms are still limited in accuracy and there is a semantic gap between automatic feature extractors and expert analyses.
Finally, I will present some strategies to address these challenges by developing methods adapted to different repertoire and defining strategies to integrate expert knowledge into computational models, as a way to build systems following a “computer-assisted” paradigm.
Dr. Emilia Gómez is postdoc researcher and assistant professor at the Music Technology Group (MTG), ICT Department in Universitat Pompeu Fabra (UPF), and graduated as a Telecommunication Engineer specialised in Signal Processing at Universidad de Sevilla. In July 2006, Emilia completed her PhD in Computer Science and Digital Communication at the UPF, on the topic of Tonal Description of Music Audio Signals. Her main research interests are related to melodic and tonal description of music audio signals, computer-assisted music analysis and computational ethnomusicology.