September 4, 2018 Dataset Open Access

Elena Agulló Cantos

DCAT Export

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        <foaf:name>Elena Agulló Cantos</foaf:name>
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    <dct:title>Flute audio labelled database for Automatic Music Transcription</dct:title>
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    <dcat:keyword>Automatic Music Transcription</dcat:keyword>
    <dcat:keyword>Music Information Retrieval</dcat:keyword>
    <dcat:keyword>Sound analysis</dcat:keyword>
    <dcat:keyword>Music</dcat:keyword>
    <dcat:keyword>Flute</dcat:keyword>
    <dcat:keyword>Digital audio</dcat:keyword>
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        <foaf:name>José Manuel Iñesta Quereda</foaf:name>
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        <foaf:name>José Javier Valero Mas</foaf:name>
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    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2018-09-04</dct:issued>
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    <dct:description>&lt;p&gt;Automatic Music Transcription (ATM) is a well-known task in the Music Information Retrieval (MIR) domain and consists on the computation of a symbolic music representation from an audio recording. In this work, our focus is to adapt algorithms that extract musical information from an audio file for a particular instrument. The main objective is to study the automatic transcription of digitized music support systems. Currently, these techniques are applied to a generic sound timbre, to sounds to any instrument for further analysis and conversion to a digital music encoding and final score format. The results of this project add new knowledge in this automatic transcription field, since traverse flute has been selected as the instrument on which to focus all the process and, until now, there is no database of flute sounds for this purpose.&lt;/p&gt; &lt;p&gt;For so, we have recorded some sounds, both monophonic and polyphonic music. These audio files have been processed by the chosen transcription algorithm and converted to a digital music encoding format for its posterior alignment with the original recordings. Once all these data have been converted to text, the resulting labeled database its constituted by the initial audios and final aligned files.&lt;/p&gt; &lt;p&gt;Furthermore, after this process and from the obtained data, an evaluation of the transcriptor behavior has been made based on two main techniques: note and frame level.&lt;/p&gt; &lt;p&gt;This database includes the original audio files (.wav),&amp;nbsp;transcribed MIDI files (.mid), aligned MIDI files (.mid), aligned text files (.txt) and evaluation files (.csv).&lt;/p&gt;</dct:description>
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