This is the video of my keynote talk at FMA 2013, titled “Towards Computer-Assisted Transcription and Description of Music Recordings”. This is the abstract of the talk. I hope you will like it!
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 music 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 present the state-of-the art on automatic transcription and description of music audio signals. I illustrate it with our own research on tonality estimation, melodic transcription and rhythmic characterization. I 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.
Moreover, I 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.