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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 6 of 6 1 Investigation of Back-off Based Interpolation Between Recurrent Neural Network and N-gram Language Models (Author's Manuscript) Chen, X; Liu,X; Gales,M J F; Woodland,P C. - 2016 Abstract: Recurrent neural network language models (RNNLMs) have become an increasingly popular choice for speech and language processing tasks including automatic speech recognition (ASR). As the generalization patterns of RNNLMs and n-gram LMs are inherently different, RNNLMs are usually combined with n-gram LMs via a fixed weighting based linear interpolation in state-of-the-art ASR systems. However, previous work doesn't fully exploit the difference of modelling power of the RNNLMs and n-gram LMs as n-gram level changes. In order to fully exploit the detailed n-gram level complementary attributes between the two LMs, a back-off based compact representation of n-gram dependent interpolation weights is proposed in this paper. This approach allows weight parameters to be robustly estimated on limited data. Experimental results are reported on the three tasks with varying amounts of training data. Small and consistent improvements in both perplexity and WER were obtained using the proposed interpolation approach over the baseline fixed weighting based linear interpolation. ; 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU) , 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU) , 13 Dec 2015, 17 Dec 2015, Presented at the 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), held in Scottsdale, AZ on 12-17 December 2015. Keyword: algorithms; artificial intelligence software; artificial neural networks; automated speech recognition; clustering; context; context modeling; digital data; history; IARPA Collection; interpolation; language model interpolation; machine translation; natural languages; perplexity; probability; probability distributions; recurrent neural network; rnnlms(Recurrent neural network language models); robustness; speech recognition; Statistics and Probability; vocabulary; Voice Communications URL: http://www.dtic.mil/docs/citations/AD1038537 http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=AD1038537 BASE Hide details 2 Robust Speech Recognition - Speaker and Noise Factorization for Robust Speech Recognition Wang, Y; Gales, M J F In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 20 (2012) 7, 2149-2158 OLC Linguistik Show details 3 Speech Synthesis and Generation - Statistical Parametric Speech Synthesis Based on Speaker and Language Factorization Zen, H; Braunschweiler, N; Buchholz, S... In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 20 (2012) 6, 1713-1724 OLC Linguistik Show details 4 Mean and variance adaptation within the MLLR framework Gales, M J F; Woodland, P C In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 10 (1996) 4, 249-264 OLC Linguistik Show details 5 Robust Continuous Speech Recognition Using Parallel Model Combination Gales, M J F; Young, S J In: Institute of Electrical and Electronics Engineers. IEEE transactions on speech and audio processing. - New York, NY : Inst. 4 (1996) 5, 352-359 OLC Linguistik Show details 6 Robust speech recognition in additive and convolutional noise using parallel model combination Gales, M J F; Young, S J In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 9 (1995) 4, 289-308 OLC Linguistik Show details

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