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Word error rate

About: Word error rate is a research topic. Over the lifetime, 11939 publications have been published within this topic receiving 298031 citations.


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Proceedings ArticleDOI
Dong Yu1, Li Deng1
27 Aug 2011
TL;DR: Results on both MNIST and TIMIT tasks evaluated thus far demonstrate superior performance of DCN over the DBN (Deep Belief Network) counterpart that forms the basis of the DNN, reflected not only in training scalability and CPU-only computation, but more importantly in classification accuracy in both tasks.
Abstract: We recently developed context-dependent DNN-HMM (DeepNeural-Net/Hidden-Markov-Model) for large-vocabulary speech recognition. While achieving impressive recognition error rate reduction, we face the insurmountable problem of scalability in dealing with virtually unlimited amount of training data available nowadays. To overcome the scalability challenge, we have designed the deep convex network (DCN) architecture. The learning problem in DCN is convex within each module. Additional structure-exploited fine tuning further improves the quality of DCN. The full learning in DCN is batch-mode based instead of stochastic, naturally lending it amenable to parallel training that can be distributed over many machines. Experimental results on both MNIST and TIMIT tasks evaluated thus far demonstrate superior performance of DCN over the DBN (Deep Belief Network) counterpart that forms the basis of the DNN. The superiority is reflected not only in training scalability and CPU-only computation, but more importantly in classification accuracy in both tasks.

163 citations

Journal ArticleDOI
TL;DR: This paper proposes methods for a tighter integration of ASR and SLU using word confusion networks (WCNs), which provide a compact representation of multiple aligned ASR hypotheses along with word confidence scores, without compromising recognition accuracy.

163 citations

Book ChapterDOI
01 Jan 1999
TL;DR: Because word_align and char_align were designed to work robustly on texts that are smaller and more noisy than the Hansards, it has been possible to successfully deploy the programs at AT&T Language Line Services, a commercial translation service, to help them with difficult terminology.
Abstract: We have developed a new program called word_align for aligning parallel text, text such as the Canadian Hansards that are available in two or more languages. The program takes the output of char_align (Church, 1993), a robust alternative to sentence-based alignment programs, and applies word-level constraints using a version of Brown et al.’s Model 2 (Brown et al., 1993), modified and extended to deal with robustness issues. Word_align was tested on a subset of Canadian Hansards supplied by Simard (Simard et al., 1992). The combination of word_align plus char_align reduces the variance (average square error) by a factor of 5 over char_align alone. More importantly, because word_align and char_align were designed to work robustly on texts that are smaller and more noisy than the Hansards, it has been possible to successfully deploy the programs at AT&T Language Line Services, a commercial translation service, to help them with difficult terminology.

163 citations

Proceedings ArticleDOI
Li Deng1, Alejandro Acero1, Li Jiang1, Jasha Droppo1, Xuedong Huang1 
07 May 2001
TL;DR: A novel technique of SPLICE (Stereo-based Piecewise Linear Compensation for Environments) for high performance robust speech recognition is described, an efficient noise reduction and channel distortion compensation technique that makes effective use of stereo training data.
Abstract: We describe a novel technique of SPLICE (Stereo-based Piecewise Linear Compensation for Environments) for high performance robust speech recognition. It is an efficient noise reduction and channel distortion compensation technique that makes effective use of stereo training data. We present a new version of SPLICE using the minimum-mean-square-error decision, and describe an extension by training clusters of hidden Markov models (HMMs) with SPLICE processing. Comprehensive results using a Wall Street Journal large vocabulary recognition task and with a wide range of noise types demonstrate the superior performance of the SPLICE technique over that under noisy matched conditions (19% word error rate reduction). The new technique is also shown to consistently outperform the spectral-subtraction noise reduction technique, and is currently being integrated into the Microsoft MiPad, a new generation PDA prototype.

163 citations

Journal ArticleDOI
TL;DR: These new techniques are shown to simultaneously achieve a multiplicative data-rate advantage and lower error rate as compared to conventional coded orthogonal-frequency division multiplexing in Rayleigh fading.
Abstract: This paper explores the improvement in information capacity and practical data rate that is possible with adaptive antenna technology applied to wireless-multipath communication channels. Whereas the conventional view is that multipath-signal propagation is an impediment to reliable communication, this paper shows that multipath can actually multiply the achievable data rate for wireless channels provided that the appropriate communication structure is employed. Multivariate discrete multitone (MDMT) combined with multivariate trellis-coded modulation (MTCM) is proposed and analyzed as a practical means of realizing a multiplicative-rate advantage in the case where channel-state information is not available at the transmitter. In Rayleigh fading, these new techniques are shown to simultaneously achieve a multiplicative data-rate advantage and lower error rate as compared to conventional coded orthogonal-frequency division multiplexing. Optimal minimum mean square error (MMSE), adaptive MDMT channel-estimation techniques are derived. The effects of channel-estimation error on MTCM are analyzed.

163 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023271
2022562
2021640
2020643
2019633
2018528