2,981 research outputs found
Development of a speech recognition system for Spanish broadcast news
This paper reports on the development process of a speech recognition system for Spanish broadcast news within the MESH FP6 project. The system uses the SONIC recognizer developed at the Center for Spoken Language Research (CSLR), University of Colorado. Acoustic and language models were trained using Hub4 broadcast news data. Experiments and evaluation results are reported
Large scale evaluations of multimedia information retrieval: the TRECVid experience
Information Retrieval is a supporting technique which underpins a broad range of content-based applications including retrieval, filtering, summarisation, browsing, classification, clustering, automatic linking, and others. Multimedia information retrieval (MMIR) represents those applications when applied to multimedia information such as image, video, music, etc. In this presentation and extended abstract we are primarily concerned with MMIR as applied to information in digital video format. We begin with a brief overview of large scale evaluations of IR tasks in areas such as text, image and music, just to illustrate that this phenomenon is not just restricted to MMIR on video. The main contribution, however, is a set of pointers and a summarisation of the work done as part of TRECVid, the annual benchmarking exercise for video retrieval tasks
A Scalable Video Search Engine Based on Audio Content Indexing and Topic Segmentation
One important class of online videos is that of news broadcasts. Most news
organisations provide near-immediate access to topical news broadcasts over the
Internet, through RSS streams or podcasts. Until lately, technology has not
made it possible for a user to automatically go to the smaller parts, within a
longer broadcast, that might interest them. Recent advances in both speech
recognition systems and natural language processing have led to a number of
robust tools that allow us to provide users with quicker, more focussed access
to relevant segments of one or more news broadcast videos. Here we present our
new interface for browsing or searching news broadcasts (video/audio) that
exploits these new language processing tools to (i) provide immediate access to
topical passages within news broadcasts, (ii) browse news broadcasts by events
as well as by people, places and organisations, (iii) perform cross lingual
search of news broadcasts, (iv) search for news through a map interface, (v)
browse news by trending topics, and (vi) see automatically-generated textual
clues for news segments, before listening. Our publicly searchable demonstrator
currently indexes daily broadcast news content from 50 sources in English,
French, Chinese, Arabic, Spanish, Dutch and Russian.Comment: NEM Summit, Torino : Italy (2011
Using term clouds to represent segment-level semantic content of podcasts
Spoken audio, like any time-continuous medium, is notoriously difficult to browse or skim without support of an interface providing semantically annotated jump points to signal the user where to listen in. Creation of time-aligned metadata by human annotators is prohibitively expensive, motivating the investigation of representations of segment-level semantic content based on transcripts
generated by automatic speech recognition (ASR). This paper
examines the feasibility of using term clouds to provide users with a structured representation of the semantic content of podcast episodes. Podcast episodes are visualized as a series of sub-episode segments, each represented by a term cloud derived from a transcript
generated by automatic speech recognition (ASR). Quality of
segment-level term clouds is measured quantitatively and their utility is investigated using a small-scale user study based on human labeled segment boundaries. Since the segment-level clouds generated from ASR-transcripts prove useful, we examine an adaptation of text tiling techniques to speech in order to be able to generate segments as part of a completely automated indexing and structuring system for browsing of spoken audio. Results demonstrate that the segments generated are comparable with human selected segment boundaries
- …