SOUND SOFTWARE: TOWARDS SOFTWARE REUSE IN AUDIO AND MUSIC RESEARCH

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Computer-aided Melody Note Transcription Using the Tony Software: Accuracy and Efficiency

accepteddate-added: 2015-05-24 19:18:46 +0000 date-modified: 2017-12-28 10:36:36 +0000 keywords: Tony, melody, note, transcription, open source software bdsk-url-1: https://code.soundsoftware.ac.uk/attachments/download/1423/tony-paper_preprint.pdfdate-added: 2015-05-24 19:18:46 +0000 date-modified: 2017-12-28 10:36:36 +0000 keywords: Tony, melody, note, transcription, open source software bdsk-url-1: https://code.soundsoftware.ac.uk/attachments/download/1423/tony-paper_preprint.pdfWe present Tony, a software tool for the interactive an- notation of melodies from monophonic audio recordings, and evaluate its usability and the accuracy of its note extraction method. The scientific study of acoustic performances of melodies, whether sung or played, requires the accurate transcription of notes and pitches. To achieve the desired transcription accuracy for a particular application, researchers manually correct results obtained by automatic methods. Tony is an interactive tool directly aimed at making this correction task efficient. It provides (a) state-of-the art algorithms for pitch and note estimation, (b) visual and auditory feedback for easy error-spotting, (c) an intelligent graphical user interface through which the user can rapidly correct estimation errors, (d) extensive export functions enabling further processing in other applications. We show that Tony’s built in automatic note transcription method compares favourably with existing tools. We report how long it takes to annotate recordings on a set of 96 solo vocal recordings and study the effect of piece, the number of edits made and the annotator’s increasing mastery of the software. Tony is Open Source software, with source code and compiled binaries for Windows, Mac OS X and Linux available from https://code.soundsoftware.ac.uk/projects/tony/

Software techniques for good practice in audio and music research

In this paper we discuss how software development can be improved in the audio and music research community by implementing tighter and more effective development feedback loops. We suggest first that researchers in an academic environment can benefit from the straightforward application of peer code review, even for ad-hoc research software; and second, that researchers should adopt automated software unit testing from the start of research projects. We discuss and illustrate how to adopt both code reviews and unit testing in a research environment. Finally, we observe that the use of a software version control system provides support for the foundations of both code reviews and automated unit tests. We therefore also propose that researchers should use version control with all their projects from the earliest stage

Software techniques for good practice in audio and music research

In this paper we discuss how software development can be improved in the audio and music research community by implementing tighter and more effective development feedback loops. We suggest first that researchers in an academic environment can benefit from the straightforward application of peer code review, even for ad-hoc research software; and second, that researchers should adopt automated software unit testing from the start of research projects. We discuss and illustrate how to adopt both code reviews and unit testing in a research environment. Finally, we observe that the use of a software version control system provides support for the foundations of both code reviews and automated unit tests. We therefore also propose that researchers should use version control with all their projects from the earliest stage

The song remains the same: Lossless conversion and streaming of MIDI to RDF and back

In this demo, we explore the potential of RDF as a representation format for digital music. Digital music is broadly used today in many professional music production environments. For decades, MIDI (Musical Instrument Digital Interface) has been the standard for digital music exchange between musicians and devices, albeit not in a Web friendly way. We show the potential of expressing digital music as Linked Data, using our midi2rdf suite of tools to convert and stream digital music in MIDI format to RDF. The conversion allows for lossless round tripping: we can reconstruct a MIDI file identical to the original using its RDF representation. The streaming uses an existing, novel generative audio matching algorithm that we use to broadcast, with very low latency, RDF triples of MIDI events coming from arbitrary analog instruments