Easy as abcDE: Piano Fingering Transcription Online
نویسنده
چکیده
Benefits • Easily deployable as a web application • Highly usable, with a what-you-see-is-what-you-get (WYSIWYG) paradigm to reduce data entry errors • Scalable for data collection on the web (no more transcription of hand-written annotations) • Configurable, with experimental design in mind • Interoperable with Qualtrics survey tool (via its JavaScript API) • Compatible with standardized, well-documented, and expressive new data file format (no need to roll your own) • Flexible with respect to input definition (abc or the popular MusicXML format) • Perfectly affordable (gratis) • Mutable as open-source software (libre) Used successfully with • Chrome • Safari • Firefox • Mobile (iOS and Android) • Desktop (OSX and Windows) • Qualtrics JavaScript API (mixed results)
منابع مشابه
Automatic Piano Reduction from Ensemble Scores Based on Merged-Output Hidden Markov Model
We discuss automated piano reduction from ensemble scores based on stochastic models of piano fingering and reduction process. Music arrangement including piano transcription is an important compositional technique, automation of which creates a challenging research field. As a starting point, we aim at a simple case of piano reduction which is playable and sounds similar to the original ensemb...
متن کاملDesign and Implementation of a Piano Practice Support System using a Real-Time Fingering Recognition Technique
Piano players need to learn various techniques such as correct keying and fingering. However, the lighted keyboards, which light up the key and are the most commonly used piano learning supports, have several problems for learners, such as difficulty in understanding the presented fingering information and flow of keying positions, and lack of a fingering check function. To resolve these proble...
متن کاملMerged-Output HMM for Piano Fingering of Both Hands
This paper discusses a piano fingering model for both hands and its applications. One of our motivations behind the study is automating piano reduction from ensemble scores. For this, quantifying the difficulty of piano performance is important where a fingering model of both hands should be relevant. Such a fingering model is proposed that is based on merged-output hidden Markov model and can ...
متن کاملDactylize: Automatically Collecting Piano Fingering Data from Performance
A prototype system, dubbed “Dactylize,” for collecting fingering data automatically from actual piano performances is described. The solution promises to be an economical and accurate tool for developing corpora related to piano fingering. Evaluation of an early prototype suggests accuracy over 99% at rates up to 12.5 notes per second.
متن کاملAutomatic Decision of Piano Fingering Based on a Hidden Markov Models
This paper proposes a Hidden Markov Model (HMM)-based algorithm for automatic decision of piano fingering. We represent the positions and forms of hands and fingers as HMM states and model the resulted sequence of performed notes as emissions associated with HMM transitions. Optimal fingering decision is thus formulated as Viterbi search to find the most likely sequence of state transitions. Th...
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تاریخ انتشار 2016