In this paper, we describe two examples of implementations of the Media Fragments URI specification which is currently being developed by the W3C Media Fragments Working Group. The group's mission is to create standard addressing schemes for media fragments on the Web using Uniform Resource Identifiers (URIs). We describe two scenarios to illustrate the implementations. More specifically, we show how User Agents (UA) will either be able to resolve media fragment URIs without help from the server, or will make use of a media fragments-aware server. Finally, we present some ongoing discussions and issues regarding the implementation of the Media Fragments specification.

Semantic interpretation of the data distributed over the Internet is subject to major current research activity. The Continuous Media Web (CMWeb) extends the World Wide Web to time-continuously sampled data such as audio and video in regard to the searching, linking, and browsing functionality. The CMWeb technology is based the file format Annodex which streams the media content interspersed with markup in the Continuous Media Markup Language (CMML) format that contains information relevant to the whole media file, e.g., title, author, language as well as time-sensitive information, e.g., topics, speakers, time-sensitive hyperlinks. The CMML markup may be generated manually or automatically. This paper investigates the automatic extraction of meta data and markup information from complex linguistic annotations, which are annotated recordings collected for use in linguistic research. We are particularly interested in annotated recordings of meetings and teleconferences and see automatically generated CMML files and their corresponding Annodex streams as one way of viewing such recordings. The paper presents some experiments with generating Annodex files from hand-annotated meeting recordings.

One of the goals of the Continuous Media Web project1 is to integrate digital media with the World Wide Web: media documents can hyperlink to and from other documents in the same way that HTML pages do. The dual capabilities of hyperlinking (1) to other documents while viewing a media clip, and (2) into precise time intervals in a media clip, enable greatly improved user interaction with media. We discuss the idea of a novel media browser application, which merges the concept of a traditional media player that presents video and audio to the user, with a Web browser that provides hyperlinking and navigation between networked (media) documents. The particular issue we address in this article concerns the primary navigational features: a media player relies on a playlist while a Web browser uses a browsing history for navigation. We discuss design and user interface issues that arise when integrating these two navigational features in a media browser.

This demonstration introduces the Annodex set of technologies, which enable the creation of Webs of audio and video resources integrated into the searching and surfing infrastructure of the World Wide Web. The demonstration covers the live creation of Annodex content and thus of Webs of video and audio, the setup of a Web server to distribute Annodex resources, the use of a Web browser to hyperlink between clips of Annodex resources, and the use of a Web search engine in which media clips can be searched through text queries.

This paper presents work on the determination of temporal audio segmentations at different semantic levels. The segmentation algorithm draws upon the calculation of relative silences or pauses. A perceptual loudness measure is the only feature employed. An adaptive threshold is used for classification into pause and non-pause. The segmentation algorithm that determines perceptually relevant pause intervals for different semantic levels incorporates a minimum duration and a maximum interruption constraint. The influence of the different parameters on the segmentation is examined in experiments and presented in this paper. A new approach for evaluating segmentation accuracies is required. It is shown that the simple perceptual pause concept has a very high relevance when segmenting audio at different semantic levels.

This paper describes the theoretic framework and applications of automatic audio content analysis.After explaining the basic properties of audio analysis, we present a toolbox being the basis for the development of audio analysis algorithms.We also describe new applications which can be developed using the toolset, among them music indexing and retrieval as well as violence detection in the sound track of videos.