History-based visual mining of semi-structured audio and text

Accessing specific or salient parts of multimedia recordings remains a challenge as there is no obvious way of structuring and representing a mix of space-based and time-based media. A number of approaches have been proposed which usually involve translating the continuous component of the multimedia recording into a space-based representation, such as text from audio through automatic speech recognition and images from video (keyframes). In this paper, we present a novel technique which defines retrieval units in terms of a log of actions performed on space-based artefacts, and exploits timing properties and extended concurrency to construct a visual presentation of text and speech data. This technique can be easily adapted to any mix of space-based artefacts and continuous media

Gathering a corpus of multimodal computer-mediated meetings with focus on text and audio interaction

In this paper we describe the gathering of a corpus of synchronised speech and text interaction over the network. The data collection scenarios characterise audio meetings with a significant textual component. Unlike existing meeting corpora, the corpus described in this paper emphasises temporal relationships between speech and text media streams. This is achieved through detailed logging and time stamping of text editing operations, actions on shared user interface widgets and gesturing, as well as generation of speech activity profiles. A set of tools has been developed specifically for these purposes which can be used as a data collection platform for the development of meeting browsers. The data gathered to data consists of nearly 30 hours of recorded audio and time stamped editing operations and gestures