Music signals are complex. When musicians play together, their instruments' sounds superimpose and form a single complex sound mixture. Furthermore, even the sound of a single instrument may already comprise sound components of harmonic, percussive, noise-like, and transient nature, among others. The complexity of music signal processing tasks such as time-scale modifcation - the task of stretching or compressing the duration of a music signal - or music source separation - the task of separating a music recording into signals that correspond to the individual instruments - is therefore often directly derived from the complexity of music signals themselves. In this thesis, our goal is to explore novel ways of approaching music signal processing tasks. One of our core ideas is to reduce a task's complexity by decomposing a given music signal into a set of two or more mid-level components and then process these components individually. Depending on the audio decomposition technique, a mid-level component may reflect certain aspects of the music signal, such as its harmonic or percussive sounds. This explicit interpretation often allows us to apply more specialized methods for processing the mid-level components. In a last step, the processed component signals are recombined to form a global result. As part of our contributions, we propose various novel audio decomposition techniques for splitting a music signal into mid-level components. For example, we present a method for decomposing a signal into three components that contain the signal's harmonic-, percussive-, and noise-like sounds, respectively. Furthermore, we apply the general strategy described previously to approach different tasks in the fields of digital signal processing and music information retrieval. In particular, we propose novel procedures for time-scale modification, singing voice separation, vibrato analysis, and audio mosaicing. Built upon these methods, we additionally present various prototype user interfaces and tools for analyzing, ...


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    Titel :

    Processing Music Signals Using Audio Decomposition Techniques ; Verarbeitung von Musiksignalen unter Verwendung von Zerlegungstechniken für Audiodaten


    Beteiligte:

    Erscheinungsdatum :

    2016-01-01


    Medientyp :

    Hochschulschrift


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629




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