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This paper describes connectionist techniques for recognition of Broadcast News. The fundamental difference between connectionist systems and more conventional mixture-of-Gaussian systems is that connectionist models directly estimate posterior probabilities as opposed to likelihoods. Access to posterior probabilities has enabled us to develop a number of(More)
THISL is an ESPRIT Long Term Research Project fo-cused the development and construction of a system to items from an archive of television and radio news broadcasts. In this paper we outline our spoken document retrieval system based on the ABBOT speech recognizer and a text retrieval system based on Okapi term-weighting. The system has been evaluated as(More)
This paper presents a real-time speech recognition system used to transcribe broadcast radio speech. The system is based on Abbot, the hybrid connectionist-HMM large vocabulary continuous speech recognition system developed at the Cambridge University Engineering Department 1]. Developments designed to make the system more robust to acoustic variability and(More)
The loss of a pregnancy in the first trimester is a common event and recent research has identified high levels of psychological distress amongst women who have miscarried. We believe this study is the first to examine the phenomenon from a longitudinal perspective using standardized measures. A sample of 65 women was rated for anxiety and depression using(More)
ABBOT is the hybrid connectionist-hidden Markov model (HMM) large-vocabulary continuous speech recognition (CSR) system developed at Cambridge University. This system uses a recurrent network to estimate the acoustic observation probabilities within an HMM framework. A major advantage of this approach is that good performance is achieved using(More)
Hybrid connectionist-hidden Markov model large vocabulary speech recognition has, in recent years, been shown to be competitive with more traditional HMM systems [4]. Connectionist acoustic models generally use considerably less parameters than HMM's, allowing real-time operation without significant degradation of performance. However, the small number of(More)
This paper describes the THISL system that participated in the TREC-7 evaluation, Spoken Document Retrieval (SDR) Track, and presents the results obtained, together with some analysis. The THISL system is based on the ABBOT speech recognition system and the thislIR text retrieval system. In this evaluation we were concerned with investigating the(More)
This paper describes the SPRACH system developed for the 1998 Hub-4E broadcast news evaluation. The system is based on the connectionist-HMM framework and uses both recurrent neural network and multi-layer perceptron acoustic models. We describe both a system designed for the primary transcription hub, and a system for the less-than 10 times real-time(More)