通过音频共享本体实现音频内容提供者的语义集成

IF 2.1 3区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Miguel Ceriani , Fabio Viola , Saša Rudan , Francesco Antoniazzi , Mathieu Barthet , György Fazekas
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引用次数: 1

摘要

各种各样的音频内容可以通过越来越多的存储库和平台在线获得。用户可以访问音乐轨道、录制声音或乐器样本等资源,用于从定制音乐聆听和探索到使用现有声音和样本进行音乐制作和声音设计等任务。然而,每个在线存储库都提供自己的API,并通过自己的数据模型表示信息,这使得应用程序很难利用网络上的在线音频和音乐内容的多样性。以灵活的方式集成音频存储库的关键一步是为其中的数据建模的共享基础。本文描述并扩展了Audio Commons Ontology,这是一种用于集成音频媒体领域现有存储库的公共数据模型。通过调查和需求分析,在用户参与的情况下设计本体,并通过演示如何支持四个相关存储库与异构api和数据模型的集成来对使用中的本体进行评估。虽然这项工作证明了音频领域的概念,但我们提出的方法可能适用于广泛的媒体集成任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Semantic integration of audio content providers through the Audio Commons Ontology

A broad variety of audio content is available online through an increasing number of repositories and platforms. Resources such as music tracks, recorded sounds or instrument samples may be accessed by users for tasks ranging from customised music listening and exploration, to music making and sound design using existing sounds and samples. However, each online repository offers its own API and represents information through its own data model, making it difficult for applications to exploit the plurality of online audio and music content on the web. A crucial step toward integrating audio repositories in a flexible manner is a shared basis for modelling the data therein. This paper describes and extends the Audio Commons Ontology, a common data model designed to integrate existing repositories in the audio media domain. The ontology is designed with the involvement of users through surveys and requirements analyses, and evaluated in-use, by demonstrating how it supports the integration of four relevant repositories with heterogeneous APIs and data models. While this work proves the concept in the audio domain, our proposed methodology may transfer across a broad range of media integration tasks.

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来源期刊
Journal of Web Semantics
Journal of Web Semantics 工程技术-计算机:人工智能
CiteScore
6.20
自引率
12.00%
发文量
22
审稿时长
14.6 weeks
期刊介绍: The Journal of Web Semantics is an interdisciplinary journal based on research and applications of various subject areas that contribute to the development of a knowledge-intensive and intelligent service Web. These areas include: knowledge technologies, ontology, agents, databases and the semantic grid, obviously disciplines like information retrieval, language technology, human-computer interaction and knowledge discovery are of major relevance as well. All aspects of the Semantic Web development are covered. The publication of large-scale experiments and their analysis is also encouraged to clearly illustrate scenarios and methods that introduce semantics into existing Web interfaces, contents and services. The journal emphasizes the publication of papers that combine theories, methods and experiments from different subject areas in order to deliver innovative semantic methods and applications.
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