Abstract / truncated to 115 words (read the full abstract)

Music was the first mass-market industry to be completely restructured by digital technology, and today we can have access to thousands of tracks stored locally on our smartphone and millions of tracks through cloud-based music services. Given the vast quantity of music at our fingertips, we now require novel ways of describing, indexing, searching and interacting with musical content. In this thesis we focus on a technology that opens the door to a wide range of such applications: automatically estimating the pitch sequence of the melody directly from the audio signal of a polyphonic music recording, also referred to as melody extraction. Whilst identifying the pitch of the melody is something human listeners can do ... toggle 25 keywords

audio content processing – auditory scene analysis – automatic music transcription – bass line – contour – evaluation methodology – flamenco – fundamental frequency – genre classification – harmony – indian classical music – melodic contour – melodic transcription – melody – melody extraction – music information retrieval – music signal processing – music similarity – pitch – pitch tracking – polyphonic – predominant melody estimation – query by humming – tonic identification – version identification

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