Thesis Open Access

From heuristics-based to data-driven audio melody extraction

Bosch, Juan J.

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    "description": "<p><strong>Abstract</strong></p>\n\n<p>The identification of the melody from a music recording is a relatively easy task for humans, but very challenging for computational systems. This task is known as &quot;audio melody extraction&quot;, more formally defined as the automatic estimation of the pitch sequence of the melody directly from the audio signal of a polyphonic music recording. This thesis investigates the benefits of exploiting knowledge automatically derived from data for audio melody extraction, by combining digital signal&nbsp;processing and machine learning methods. We extend the scope of melody extraction research by working with a varied dataset and multiple definitions of melody. We first present an overview of the state of the art, and perform an evaluation focused on a novel symphonic music dataset. We then propose melody extraction methods based on a source-filter model and pitch contour characterisation and evaluate them on a wide range of music genres. Finally, we explore novel timbre, tonal and spatial features for contour characterisation, and propose a method for estimating multiple melodic lines. The combination of supervised and unsupervised approaches leads to advancements on melody extraction and shows a promising path for future research and applications.</p>\n\n<p>&nbsp;</p>\n\n<p><strong>Datasets:&nbsp;</strong><br>\n<br>\nThe symphonic music dataset proposed in this thesis (Orchset) is available at:</p>\n\n<p><a href=\"\"></a></p>\n\n<p>Orchset is intended to be used as a dataset for the development and evaluation of melody extraction algorithms. This collection contains 64 audio excerpts focused on symphonic music. with their corresponding annotation of the melody.</p>\n\n<p><strong>Code:</strong></p>\n\n<p>The source code of the melody extraction algorithms proposed in this thesis is available at:</p>\n\n<p><a href=\"\"></a></p>", 
    "language": "eng", 
    "title": "From heuristics-based to data-driven audio melody extraction", 
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    "thesis": {
      "university": "Universitat Pompeu Fabra, Barcelona", 
      "supervisors": [
          "affiliation": "Universitat Pompeu Fabra, Barcelona", 
          "name": "G\u00f3mez, Emilia"
    "keywords": [
      "Melody Extraction", 
    "publication_date": "2017-06-27", 
    "creators": [
        "orcid": "0000-0003-4221-3517", 
        "affiliation": "Universitat Pompeu Fabra, Barcelona", 
        "name": "Bosch, Juan J."
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