Indexing and retrieval of broadcast news

This paper describes a spoken document retrieval (SDR) system for British and North American Broadcast News. The system is based on a connectionist large vocabulary speech recognizer and a probabilistic information retrieval system. We discuss the development of a realtime Broadcast News speech recognizer, and its integration into an SDR system. Two advances were made for this task: automatic segmentation and statistical query expansion using a secondary corpus. Precision and recall results using the Text Retrieval Conference (TREC) SDR evaluation infrastructure are reported throughout the paper, and we discuss the application of these developments to a large scale SDR task based on an archive of British English broadcast news

TwNC: a Multifaceted Dutch News Corpus

This contribution describes the Twente News Corpus (TwNC), a multifaceted corpus for Dutch that is being deployed in a number of NLP research projects among which tracks within the Dutch national research programme MultimediaN, the NWO programme CATCH, and the Dutch-Flemish programme STEVIN.\ud \ud The development of the corpus started in 1998 within a predecessor project DRUID and has currently a size of 530M words. The text part has been built from texts of four different sources: Dutch national newspapers, television subtitles, teleprompter (auto-cues) files, and both manually and automatically generated broadcast news transcripts along with the broadcast news audio. TwNC plays a crucial role in the development and evaluation of a wide range of tools and applications for the domain of multimedia indexing, such as large vocabulary speech recognition, cross-media indexing, cross-language information retrieval etc. Part of the corpus was fed into the Dutch written text corpus in the context of the Dutch-Belgian STEVIN project D-COI that was completed in 2007. The sections below will describe the rationale that was the starting point for the corpus development; it will outline the cross-media linking approach adopted within MultimediaN, and finally provide some facts and figures about the corpus

News story segmentation in the Físchlár video indexing system

This paper presents an approach to segmenting individual news stories in broadcast news programmes. The approach first performs shot boundary detection and keyframe extraction on the programme. Shots are then clustered into groups based on their colour and temporal similarity. The clustering process is controlled using the groups' statistics. After clustering, a set of criteria are applied and groups are successively eliminated in order to converge upon a set of anchorperson groups. The temporal locations of the shots in these anchorperson groups are then used to segment the programme in terms of individual news items. This work is carried out within the context of a complete video indexing, browsing and retrieval syste

InfoLink: analysis of Dutch broadcast news and cross-media browsing

In this paper, a cross-media browsing demonstrator named InfoLink is described. InfoLink automatically links the content of Dutch broadcast news videos to related information sources in parallel collections containing text and/or video. Automatic segmentation, speech recognition and available meta-data are used to index and link items. The concept is visualised using SMIL-scripts for presenting the streaming broadcast news video and the information links

Robust audio indexing for Dutch spoken-word collections

Abstract—Whereas the growth of storage capacity is in accordance with widely acknowledged predictions, the possibilities to index and access the archives created is lagging behind. This is especially the case in the oral history domain and much of the rich content in these collections runs the risk to remain inaccessible for lack of robust search technologies. This paper addresses the history and development of robust audio indexing technology for searching Dutch spoken-word collections and compares Dutch audio indexing in the well-studied broadcast news domain with an oral-history case-study. It is concluded that despite significant advances in Dutch audio indexing technology and demonstrated applicability in several domains, further research is indispensable for successful automatic disclosure of spoken-word collections

Spoken content retrieval: A survey of techniques and technologies

Speech media, that is, digital audio and video containing spoken content, has blossomed in recent years. Large collections are accruing on the Internet as well as in private and enterprise settings. This growth has motivated extensive research on techniques and technologies that facilitate reliable indexing and retrieval. Spoken content retrieval (SCR) requires the combination of audio and speech processing technologies with methods from information retrieval (IR). SCR research initially investigated planned speech structured in document-like units, but has subsequently shifted focus to more informal spoken content produced spontaneously, outside of the studio and in conversational settings. This survey provides an overview of the field of SCR encompassing component technologies, the relationship of SCR to text IR and automatic speech recognition and user interaction issues. It is aimed at researchers with backgrounds in speech technology or IR who are seeking deeper insight on how these fields are integrated to support research and development, thus addressing the core challenges of SCR

Indexing spoken audio by LSA and SOMs

This paper presents an indexing system for spoken audio documents. The framework is indexing and retrieval of broadcast news. The proposed indexing system applies latent semantic analysis (LSA) and self-organizing maps (SOM) to map the documents into a semantic vector space and to display the semantic structures of the document collection. The SOM is also used to enhance the indexing of the documents that are difficult to decode. Relevant index terms and suitable index weights are computed by smoothing the document vectors with other documents which are close to it in the semantic space. Experimental results are provided using the test data of the TREC's spoken document retrieval (SDR) track

Exploration of audiovisual heritage using audio indexing technology

This paper discusses audio indexing tools that have been implemented for the disclosure of Dutch audiovisual cultural heritage collections. It explains the role of language models and their adaptation to historical settings and the adaptation of acoustic models for homogeneous audio collections. In addition to the benefits of cross-media linking, the requirements for successful tuning and improvement of available tools for indexing the heterogeneous A/V collections from the cultural heritage domain are reviewed. And finally the paper argues that research is needed to cope with the varying information needs for different types of users