The 1997 Abbot System For The Transcription Of Broadcast News

This paper describes the development of a connectionist-hidden Markov model (HMM) system for the 1997 DARPA Hub-4E CSR evaluations. We describe both system development and the enhancements designed to improve performance on broadcast news data. Both multilayer perceptron (MLP) and recurrent neural network acoustic models have been investigated. We assess the effect of using gender-dependent acoustic models, and the impact on performance of varying both the number of parameters and the amount of training data used for acoustic modelling. The use of contextdependent phone models is described, and the effect of the number of context classes is investigated. We also describe a method for incorporating syllable boundary information during search. Results are reported on the 1997 DARPA Hub-4E development test set. We then describe the CU-CON evaluation system and report results on the 1997 Hub-4E test set. 1. Introduction This paper describes experiments aimed at improving the performance o..

Transcription Of Broadcast Television And Radio News: The 1996 Abbot System

ABBOT is a hybrid connectionist-HMM large vocabulary continuous speech recognition system developed at the Cambridge University Engineering Department. This uses a recurrent neural network acoustic model to map acoustic features into posterior phone probabilities. These posterior probabilities are then converted to scaled likelihoods and used as observation likelihoods for phone HMMs [1, 2]. This paper describes the development of the CUCON system which participated in the 1996 ARPA Hub 4 Evaluations. The system is based on ABBOT. The Hub 4 Evaluation task involves the transcription of broadcast television and radio news programmes. This is an extremely demanding task for state-of-the-art speech recognition systems. Typical programmes include a wide variety of speaking styles and acoustic conditions. These range from read speech recorded in the studio to extemporaneous speech recorded over telephone channels. Results are presented for the system at various stages of development, as we..

Enhancing Distributed Systems with Low-Latency Networking

Recently several network technologies which support user-level communication between processes using a shared-memory interface have become available [4, 7]. These technologies o#er very low latency, high bandwidth communication by eliminating the need for software protocol stacks. Whilst there has been much research on the use of such networks in the context of parallel computing [5, 6, 13], relatively little work has been done on their suitability for distributed applications. This paper describes the work undertaken to integrate the Scalable Coherent Interface (SCI) interconnect with the standard NFS server and a CORBA 2.0 compliant ORB over Linux. It is shown that impressive performance increases can be achieved without modification to either the operating system or the distributed application. Keywords: SCI, CORBA, NFS. 1 Introduction The computing environment at the Olivetti & Oracle Research Laboratory (ORL) is highly heterogenous, supporting our work in multimedia and sensor d..