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# (4) execute the query and convert into Python objectsįor res in results : In particular we will use DBPedia and the SPARQL-Wrapper library in Python, and Sonic Annotator.Īnd test it by executing the python code: # import the libraryįrom SPARQLWrapper import SPARQLWrapper, JSON Short hands on sessions will guide those who are new to Semantic Audio or the Semantic Web to access Linked Data resources (SPARQL end-points) and use high level tools for extracting meaningful information from audio content. The tutorial slides are available in pdf. Short Hands on Session (2) demonstrating the use of Sonic Annotator and SAWA.
#NNLS CHROMA CHORD DICTIONARY HOW TO#
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This tutorial is targeted at researchers or students in Semantic Audio Analysis and Music Information Retrieval who may benefit from using the Web of Linked data as well as semantic audio tools that utilise Semantic Web technologies. The areas around the intersection of Semantic Audio and the Semantic Web are described in more detail. This tutorial focuses on the intersection of the fields of Semantic Audio and the Semantic Web.įig 1. We will explore how signal processing tools and results can be described as structured data and utilised in audio production. Using practical examples, we will demonstrate the use of the Music and Studio Ontologies, and show how they facilitate interoperability between audio applications and linked data sets on the Web. We will outline the use of the Resource Description Framework (RDF) and related ontology and query languages. This tutorial will provide an introduction to Semantic Web concepts and how they can be used in the context of music-related studies. Recent efforts have brought this framework to bear on the field of Semantic Audio, as well as information management in audio applications.
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The emerging Semantic Web provides a powerful framework for the expression and reuse of structured data. 132nd AES Convention, 26th-29th of April, Budapest, Hungary