Dutch speech recognition in multimedia information retrieval

As data storage capacities grow to nearly unlimited sizes thanks to ever ongoing hardware and software improvements, an increasing amount of information is being stored in multimedia and spoken-word collections. Assuming that the intention of data storage is to use (portions of) it some later time, these collections must also be searchable in one way or another

Distributed Access to Oral History collections: Fitting Access Technology to the needs of Collection Owners and Researchers

In contrast with the large amounts of potential interesting research material in digital multimedia repositories, the opportunities to unveil the gems therein are still very limited. The Oral History project ‘Verteld Verleden’ (Dutch literal translation of Oral History) that is currently running in The Netherlands, focuses on improving access to spoken testimonies in collections, spread over many Dutch cultural heritage institutions, by deploying modern technology both concerning infrastructure and access. Key objective in the project is mapping the various specific requirements of collection owners and researchers regarding both publishing and access by means of current state-of-the-technology. In order to demonstrate the potential, Verteld Verleden develops an Oral History portal that provides access to distributed collections. At the same time, practical step-by-step plans are provided to get to work with modern access technologies. In this way, a solid starting point for sustained access to Oral History collections can be established

Filtering the Unknown: Speech Activity Detection in Heterogeneous Video Collections

In this paper we discuss the speech activity detection system that we used for detecting speech regions in the Dutch TRECVID video collection. The system is designed to filter non-speech like music or sound effects out of the signal without the use of predefined non-speech models. Because the system trains its models on-line, it is robust for handling out-of-domain data. The speech activity error rate on an out-of-domain test set, recordings of English conference meetings, was 4.4%. The overall error rate on twelve randomly selected five minute TRECVID fragments was 11.5%

UTwente does Rich Speech Retrieval at MediaEval 2011

This paper describes the participation of the University of Twente team at the Rich Text Retrieval Task of the Media Eval Benchmark Initiative 2011. The goal of the task is to find entry points of relevant parts of videos to reduce the browsing effort of searchers. This is our first participation, therefore our main focus is to create a baseline system which can be improved in the future. We experiment with different evidence sources (ASR and meta data) together with a basic score combination function. We also experiment with different entry points relative to the segments found by the contained evidence

Audiovisual Archive Exploitation in the Networked Information Society

Safeguarding the massive body of audiovisual content, including rich music collections, in audiovisual archives and enabling access for various types of user groups is a prerequisite for unlocking the social-economic value of these collections. Data quantities and the need for specific content descriptors however, force archives to re-evaluate their annotation strategies and access models, and incorporate technology in the archival workflow. It is argued that this can only be successfully done provided that user requirements are studied well and that new approaches are introduced in a well-balanced manner, fitting in with traditional archival perspectives, and by bringing the archivist in the technology loop by means of education and by deploying hybrid work-flows for technology aided annotation

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

Fast N-Gram Language Model Look-Ahead for Decoders With Static Pronunciation Prefix Trees

Decoders that make use of token-passing restrict their search space by various types of token pruning. With use of the Language Model Look-Ahead (LMLA) technique it is possible to increase the number of tokens that can be pruned without loss of decoding precision. Unfortunately, for token passing decoders that use single static pronunciation prefix trees, full n-gram LMLA increases the needed number of language model probability calculations considerably. In this paper a method for applying full n-gram LMLA in a decoder with a single static pronunciation tree is introduced. The experiments show that this method improves the speed of the decoder without an increase of search errors.\u