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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Score-informed musical source separation and reconstruction

Han, Yushen 26 February 2014 (has links)
<p>A systematic approach to retrieve individual parts in a monaural music recording with its score is introduced. We are interested in isolating the accompaniment part by removing the solo part from a recording of concerto music in which a solo instrument is accompanied by an orchestra. We require the music audio, the score, and optionally a sample library of individual notes played in isolation. Our approach is based on explicit knowledge of the musical audio at the semantic level (notes or chords) from an audio-score alignment. Such knowledge allows the spectrogram energy to be decomposed into note-based models that could be trained with the sample library. Our approach can be divided into: (1) "masking" to estimate a solo mask to remove the solo and (2) "reconstruction" to impute the missing harmonics of the orchestra notes that have been inevitably damaged in masking. </p><p> In "masking," we estimate a 2-dimensional binary mask to classify each time-frequency cell of the short-time Fourier Transform (STFT) spectrogram as either solo or accompaniment in STFT domain. We mainly employ an Expectation Maximization (EM) algorithm to decompose spectrogram magnitude into note-based models. In this process of "erasing" the soloist&rsquo;s contribution to the mixture by applying the mask, the remaining orchestra is degraded. In "reconstruction," we propose a novel technique to repair such degradation. We use a state-space model for each note partial which is represented by a slowing-changing amplitude envelope and an "unwrapped" phase sequence. Such amplitude-phase representation can be computed by Kalman smoothing. It allows us to "transpose" intact partials of the orchestra part onto the degraded time-frequency region. Objective metrics and subjective listening are used on real and synthesized musical audio data for evaluation and parameter optimization. </p>

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