recurrent neural network based language model interspeech 2010

... Hz). (a) Neural- network- based SVM. (b) Equivalent DSP -based SVM. Fig. 11. Machine line voltage and phase current waves in mode 2 (40 Hz). (a) Neural- network- based SVM. (b) Equivalent DSP -based SVM. ... FOR N EURAL N ETWORK Neural- network- based SVM for a two-level inverter has been described in the literature [2], [3]. It will now be extended to a 0093-9994/02$17.00 © 2002 IEEE MONDAL et al.: A NEURAL- NETWORK- BASED ... Volts/Hz-controlled drive dynamic performance with (a) neural- network- based SVM and (b) equivalent DSP -based SVM. the ANN operates at a higher resolution. The network is solved every sampling time to establish...

Ngày tải lên: 22/12/2013, 08:16

... | (1) The language model weight λ and the word inser- tion penalty ip lead to a better performance in prac- tice, but they have no theoretical justification. Our grammar -based language model is ... grammar -based language model. To this end, we used a baseline speech recognition system which provided the N best hypotheses of an utterance along with their respective scores. The grammar- based language ... of phrases or words is computed. 2.4 Model Parameters Besides the distributions required to specify P (T ), our language model has three parameters: the lan- guage model weight µ, the attachment probability q...

Ngày tải lên: 17/03/2014, 02:20

... tested this hy- pothesis by using a separate neural network to ar- bitrate among multiple detection networks. It was found that the neural network- based arbitrationpro- duces results comparable ... Kanade tk@cs.cmu.edu http://www.cs.cmu.edu/˜tk Abstract We present a neural network- based face detection system. A retinally connected neural network ex- amines small windows of an image, and decides whether ... outputfroma single network are shown in Figure 2. In the figure, each box represents the position and size of a window to which the neural network gave a positive response. The network has some...

Ngày tải lên: 28/04/2014, 09:58

... recognition/detection by probabilis- tic decision -based neural network. IEEE Transactions on Neural Networks, Special Issue on Artificial Neural Networks and Pattern Recognition, 8(1), January 1997. [ Moghaddam ... Zhang and John Fulcher. Face recognition using artificial neural network group -based adaptive tolerance (GAT) trees. IEEE Transactions on Neural Networks, 7(3):555–567, 1996. 13 Figure 4: Left: Average ... 4: Networks trained with derotated examples, but applied at all 18 orientations. Upright Test Set Rotated Test Set System Detect % # False Detect % # False Network 1 90.6% 9140 97.3% 3252 Network...

Ngày tải lên: 28/04/2014, 09:58

... Artificial neural networks for feature extraction and multivariate data projection. IEEE Trans. Neural Networks 6, 296 –317, 1995. [2] B. Lerner, Toward a completely automatic neural network based human ... 28, Part B, Special issue on artificial neural networks, 544-552, 1998. [3] B. Lerner, H. Guterman, Mayer Aladjem, A comparative study of neural network based feature extraction paradigms. Pattern Recognition. ... Multi-MLP Multi-MLP was the one that had 16 neural networks each of which had only two classes. The training files were different to each of these networks. Each network was 0-7803-7278-6/02/$10.00 ©2002...

Ngày tải lên: 28/04/2014, 10:10

... the NN. Several Network topologies are tested and their accuracy is compared. The most successful version of the NN based HSV system uses a single MLP with one hidden layer to model each user’s ... with Hidden Markov Models. Proceedings of the 14th International Conference on Pattern Recognition, Brisbane, Australia, pp 1309–1312, 1998. [5] L. Fausett. Fundamentals of Neural Networks. Prentice ... Back-propagation Neural Networks. Proceedings of the Sixth International Conference on Document Analysis and Recognition, pp 992, 2001. [10] L. Ma, T. Tan, Y. Wand and D. Zhang. Personal Identification Based...

Ngày tải lên: 28/04/2014, 10:11

... on neural network based classification. Then we summarize the classification problems, occurring when dealing with signatures, and propose solutions for them. In this paper a complete neural ... 0.5 1.1 300x300 0.2 0.5 1.4 0.3 2.0 0.5 1.3 330x330 0.1 0.3 1.9 0.2 1.2 0.2 1.7 Neural Network- based Offline Handwritten Signature Verification System using Hu’s Moment Invariant Analysis ... and Advanced Technology (IJEAT) ISSN: 2249 – 8958, Volume-1, Issue-1, October 2011 73 Neural Network- based Offline Handwritten Signature Verification System using Hu’s Moment Invariant Analysis...

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Ngày tải lên: 29/12/2013, 11:17

... and comparison of models. Journal of Geophysical Research 90 (C5), 8995–9005. Yao, X., 1999. Evolving artificial neural networks. Proceedings of the IEEE Transactions on Neural Networks 87 (9), ... concentration). Neural networks, in particular the multi-layer perceptron (Hornik et al., 1989), provide a flexible and non-linear tool for tackling regression problems in the air quality modelling ... (Hornik et al., 1989), which states that a two- hidden layer network may achieve the same accuracy with a single hidden layer neural network with fewer hidden layer neurons. However, the use of...

Ngày tải lên: 17/02/2014, 22:20

... applicable to various language families including agglutinative languages (Korean, Turkish, Finnish), highly inflected languages (Russian, Czech) as well as semitic languages (Arabic, Hebrew). ... inferred. We would like to thank Martin Franz for discussions on language model building, and his help with the use of ViaVoice language model toolkit. References Beesley, K. 1996. Arabic Finite-State ... Prefix*-Stem-Suffix* 3 Morpheme Segmentation 3.1 Trigram Language Model Given an Arabic sentence, we use a trigram language model on morphemes to segment it into a sequence of morphemes...

Ngày tải lên: 08/03/2014, 04:22

... "Class- Based n-gram Models of Natural Language& quot;. Computational Linguistics, 18(4):467-480. C. Chang and C. Chen. 1996. "Application Is- sues of SA-class Bigram Language Models". ... Preliminary experiments We have experimented with three language models, tri-gram model (TRI), bi-gram model (BI), and the proposed model (DEP) on a raw corpus extracted from KAIST corpus ... useful than the naive word sequences of n-gram, for language modeling. We are planning to experiment the perfor- mance of the proposed language model for large corpus, for various domains, and...

Ngày tải lên: 08/03/2014, 05:21

... G 0 ). 3 Hierarchical Pitman-Yor Language Models We describe an n-gram language model based on a hierarchical extension of the Pitman-Yor process. An n-gram language model defines probabilities over ... increasing as the length of the 988 Our model is a direct generalization of the hierar- chical Dirichlet language model of (MacKay and Peto, 1994). Inference in our model is however not as straightforward ... of nonpara- metric Bayesian models. Here we give a quick de- scription of the Pitman-Yor process in the context of a unigram language model; good tutorials on such models are provided in (Ghahramani,...

Ngày tải lên: 17/03/2014, 04:20

... Linguistics Fast and Scalable Decoding with Language Model Look-Ahead for Phrase -based Statistical Machine Translation Joern Wuebker, Hermann Ney Human Language Technology and Pattern Recognition ... programming beam search in phrase -based statistical machine translation (SMT), aiming at increased effi- ciency of decoding by minimizing the number of language model computations and hypothe- sis ... number of language model computations and hypothe- sis expansions. Our results show that language model based pre-sorting yields a small im- provement in translation quality and a speedup by a...

Ngày tải lên: 23/03/2014, 14:20

... a separately trained N-gram model into the system. 4 Incorporating an N -gram language model Since the seminal work of the IBM models (Brown et al., 1993), N -gram language models have been used as ... the syntax -based generation sys- tem, the incorporation of an N -gram language model can potentially improve the local fluency of output sequences. In addition, the N -gram language model can be ... amount of data, while the syntax -based model requires manual annotation for training. The standard method for the combination of a syntax model and an N -gram model is linear interpolation. We...

Ngày tải lên: 31/03/2014, 21:20