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.