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Abstract for wu_tr94
mi.eng.cam.ac.uk/reports/abstracts/wu_tr94.html27 Jul 2020: These tests have shown the applicability of nonlinear prediction to speech coding and the improvement in coding performance. -
Abstract for tuerk_tr402
mi.eng.cam.ac.uk/reports/abstracts/tuerk_tr402.html27 Jul 2020: In a number of test cases this algorithm is shown to converge reliably to the correct results. | -
Abstract for evermann_icassp2004
mi.eng.cam.ac.uk/reports/abstracts/evermann_icassp2004.html27 Jul 2020: The final 2003 CU-HTK CTS system constructed from some of these models is described and its performance on the DARPA/NIST 2003 Rich Transcription (RT-03) evaluation test set is -
Abstract for gales_tr154
mi.eng.cam.ac.uk/reports/abstracts/gales_tr154.html27 Jul 2020: This mismatch' function is then used to estimate the difference in channel conditions between training and test environments. -
Abstract for lovell_tr299
mi.eng.cam.ac.uk/reports/abstracts/lovell_tr299.html27 Jul 2020: Given insufficient training data, such a model's test set performance will be lower than that of a suitably biased model. -
Abstract for odell_darpa99
mi.eng.cam.ac.uk/reports/abstracts/speech/odell_darpa99.html27 Jul 2020: On the 1998 test the system produced an average word error rate of 16.1% running in 9.5xRT. | -
Abstract for waterhouse_hme
mi.eng.cam.ac.uk/reports/abstracts/waterhouse_hme.html27 Jul 2020: In this paper we extend the HME to classification and results are reported for three common classification benchmark tests: Exclusive-Or, N-input Parity and Two Spirals. -
Abstract for niesler_tr265
mi.eng.cam.ac.uk/reports/abstracts/niesler_tr265.html27 Jul 2020: Abstract for niesler_tr265. Cambridge University Engineering Department Technical Report CUED/F-INFENG/TR265. COMPARATIVE EVALUATION OF WORD- AND CATEGORY-BASED LANGUAGE MODELS. Thomas Niesler and Phil Woodland. July 1996. Conventional n-gram -
Abstract for woodland_rt02
mi.eng.cam.ac.uk/reports/abstracts/speech/woodland_rt02.html27 Jul 2020: Results are presented for the 2001 development test set and the 2002 evaluation set. -
Abstract for james_icassp94
mi.eng.cam.ac.uk/reports/abstracts/james_icassp94.html27 Jul 2020: The results show that the proposed method is very much faster yet performs acceptably compared to conventional systems which depend on keyword-specific training or prior knowledge of the test set
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