Information retrieval from audio data is sharply different from information retrieval from text, not simply because speech recognition errors affect retrieval effectiveness, but more fundamentally because of the linear nature of speech, and of the differences in human capabilities for processing speech versus text. We describe SCAN, a prototype speech retrieval and browsing system that addresse...

There have been two Text REtrieval conferences frRECs); TREC-1 in November 1992, with 28 participants, and TREC-2 in August 1993, with 31 participants. This conference was inspired by the very successful MUC effort, and by the availability of the new large English test collection built for TIPSTER. Whereas an important goal for ARPA was to investigate a broad range of detection (retrieval) tech...

This paper proposes an ad hoc retrieval method for spoken documents that uses a statistical translation technique. After transcribing the spoken documents by using a Large-Vocabulary Continuous Speech Recognition (LVCSR) decoder, a text-based ad hoc retrieval method can be directly applied to the transcribed documents. However, recognition errors will signi cantly degrade the retrieval performa...

Efficient indexing and retrieval of digital video is an important aspect of video databases. One powerful index for retrieval is the text appearing in them. It enables contentbased browsing. We present our methods for automatic segmentation and recognition of text in digital videos. The algorithms we propose make use of typical characteristics of text in videos in order to enable and enhance se...

DCU participated in the ImageCLEF 2008 photo retrieval task, which aimed to evaluate diversity in Image Retrieval, submitting runs for both the English and Random language annotation conditions. Our approaches used text-based and image-based retrieval to give baseline runs, with the the highest-ranked images from these baseline runs clustered using K-Means clustering of the text annotations, wi...

This paper describes our system participated in the Japanese and English Retrieval Subtasks at the NTCIR-6 Patent Retrieval Task. The purpose of these subtasks is the invalidity search, in which a patent application including a target claim is used to search documents that can invalidate the demand in the claim. Although we use a regular text-based retrieval method for the Japanese Retrieval Su...

This paper describes the first participation of the SINAI group of the University of Jaén in TRECVID 2007. We have only participated in the automatic search task. Our approach is a very simple system made up of three main modules: the text-based retrieval subsystem, the image-based retrieval subsystem and the fusion module. We have submitted several runs exploring fusion of both textual and vis...

The primary goal of the SMART information retrieval project at CorneU University remains, as it has for the past 30 years, investigating the effectiveness and efficiency of automatic methods of retrieval of text. In recent years this has expanded to include retrieval of parts of documents in response to both user queries (passage retrieval) and parts of other documents (automatic hypertext link...

This paper describes our participation at the ImageCLEF photographic retrieval task. We used our Xtrieval framework for the preparation and execution of the experiments. This year, we submitted 4 experiments in total. The experiments showed that our thesaurus based query expansions works well in improving the geometric mean average precision (GMAP) and binary preference (BPREF), but deteriorate...

We present a probabilistic model for the retrieval of multimodal documents. The model is based on Bayesian decision theory and combines models for text-based search with models for visual search. The textual model is based on the language modelling approach to text retrieval, and the visual information is modelled as a mixture of Gaussian densities. Both models have proved successful on various...