A database for the industrial trawl fishery of Cote d'Ivoire

Fishery statistics for the industrial trawl fishery of Cote d'Ivoire have been well documented since 1968. However, data processing has changed significantly with time and some of the data files have been lost. In 1997, the Centre de Recherches Oceanologiques d'Abidjan decided to retrieve and process all trawl data available from different sources. This paper gives an overview of the database covering the period 1968 to 1997 and describes its coverage, format, structure and use. The database was developed using MS ACCESS and is a powerful tool for storing information about this fishery, and for analysis of its dynamics over a period of 30 years.

A relational database of post-harvest fish losses

The article describes FISHLOSS, a database of post-harvest fish losses devised by the Natural Resources Institute (NRI), UK. The database contains 450 records of post-harvest fish losses from 150 sources. The majority of the estimates are shelf-life estimates. Designed to be a reference for people studying post-harvest fish losses, it draws attention to areas requiring future research to identify significant losses and the factors which cause them. All researchers and users are encouraged to send NRI their own estimates for inclusion in revised versions of FISHLOSS.

Mersey Estuary baseline survey. Analysis of macroinfaunal samples, literature review and database production

This is the Mersey Estuary baseline survey: Analysis of macroinfaunal samples, literature review and database production report produced by the Environment Agency North West in 2002. This report presents an ecological review of the Mersey estuary along with an extensive bibliography of the available environmental literature for this system. The central objective of this programme has been to provide the information necessary to support the Environment Agency's review of existing and future consents (for discharges, abstractions etc) in the Mersey estuary. This review of consents was required because the Mersey had been designated as a Special Protection Area (SPA) under the EC Birds Directive. Therefore under Regulation 50 of the Conservation, the Environment Agency was responsible for reviewing any extant consent, or future applications, which may directly or indirectly, affected this SPA.

The use of syntax and multiple alternatives in the VODIS voice operated database inquiry system

The paper describes the architecture of VODIS, a voice operated database inquiry system, and presents some experiments which investigate the effects on performance of varying the level of a priori syntactic constraints. The VODIS system includes a novel mechanism for incorporating context-free grammatical constraints directly into the word recognition algorithm. This allows the degree of a priori constraint to be smoothly varied and provides for the controlled generation of multiple alternatives. The results show that when the spoken input deviates from the predefined task grammar, a combination of weak a priori syntax rules in conjunction with full a posteriori parsing on a lattice of alternative word matches provides the most robust recognition performance. © 1991.

Continuous speech recognition for the TIMIT database using neural networks

Four types of neural networks which have previously been established for speech recognition and tested on a small, seven-speaker, 100-sentence database are applied to the TIMIT database. The networks are a recurrent network phoneme recognizer, a modified Kanerva model morph recognizer, a compositional representation phoneme-to-word recognizer, and a modified Kanerva model morph-to-word recognizer. The major result is for the recurrent net, giving a phoneme recognition accuracy of 57% from the si and sx sentences. The Kanerva morph recognizer achieves 66.2% accuracy for a small subset of the sa and sx sentences. The results for the word recognizers are incomplete.

MMI training for continuous phoneme recognition on the TIMIT database

This paper reports our experiences with a phoneme recognition system for the TIMIT database which uses multiple mixture continuous density monophone HMMs trained using MMI. A comprehensive set of results are presented comparing the ML and MMI training criteria for both diagonal and full covariance models. These results using simple monophone HMMs show clear performance gains achieved by MMI training, and are comparable to the best reported by others including those which use context-dependent models. In addition, the paper discusses a number of performance and implementation issues which are crucial to successful MMI training.