Tag Archives: music transcription

14/02/2017 · 15:21

Journal paper and open dataset for source separation in Orchestra music

As part of the PHENICX project, we have recently published our research results in the task of audio sound source separation, which is the main research topic of one of our PhD students, Marius Miron.

During this work, we developed a method for orchestral music source separation along with a new dataset: the PHENICX-Anechoic dataset. The methods were integrated into the  PHENICX project for tasks as orchestra focus/instrument enhancement. To our knowledge, this is the first time source separation is objectively evaluated in such a complex scenario. 

This is the complete reference to the paper:

M. Miron, J. Carabias-Orti, J. J. Bosch, E. Gómez and J. Janer, “Score-informed source separation for multi-channel orchestral recordings”, Journal of Electrical and Computer Engineering (2016))”

Abstract: This paper proposes a system for score-informed audio source separation for multichannel orchestral recordings. The orchestral music repertoire relies on the existence of scores. Thus, a reliable separation requires a good alignment of the score with the audio of the performance. To that extent, automatic score alignment methods are reliable when allowing a tolerance window around the actual onset and offset. Moreover, several factors increase the difficulty of our task: a high reverberant image, large ensembles having rich polyphony, and a large variety of instruments recorded within a distant-microphone setup. To solve these problems, we design context-specific methods such as the refinement of score-following output in order to obtain a more precise alignment. Moreover, we extend a close-microphone separation framework to deal with the distant-microphone orchestral recordings. Then, we propose the first open evaluation dataset in this musical context, including annotations of the notes played by multiple instruments from an orchestral ensemble. The evaluation aims at analyzing the interactions of important parts of the separation framework on the quality of separation. Results show that we are able to align the original score with the audio of the performance and separate the sources corresponding to the instrument sections.

The PHENICX-Anechoic dataset includes audio and annotations useful for different MIR tasks as score-informed source separation, score following, multi-pitch estimation, transcription or instrument detection, in the context of symphonic music. This dataset is based on the anechoic recordings described in this paper:

Pätynen, J., Pulkki, V., and Lokki, T., “Anechoic recording system for symphony orchestra,” Acta Acustica united with Acustica, vol. 94, nr. 6, pp. 856-865, November/December 2008.

For more information about the dataset and how to download you can access the PHENICX-Anechoic web page.

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22/05/2014 · 11:04

Forum on transcription in the journal “Twentieth-Century Music”

I contributed by means of an enriching interview to the “Forum on Transcription”, authored by Jason Stanyek (University of Oxford) in the journal Twentieth-Century Music. As stated on the web site, this journal disseminates research on all aspects of music in the long twentieth century to a broad readership. Emphasis is placed upon the presentation of the full spectrum of scholarly insight, with the goal of fostering exchange and debate between disciplinary fields.

I share an interesting conversation about transcription with Parag Chordia. In this conversation with Jason we discussed about the challenges and potential of audio analysis tools for computer-assisted transcription and description of music recordings. I gave some examples on my work on the transcription of flamenco singing that is being carried out within the COFLA project. 

You can find the results of the forum and the rest of a very impressive special issue on transcription on the web.

 

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Video

Video of my keynote talk at the 3rd International Workshop on Folk Music Analysis 2013

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.

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12/07/2013 · 12:56