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LatticeRnn: Recurrent Neural Networks Over Lattices
We present a new model called LATTICERNN, which generalizes recurrent neural networks (RNNs) to process weighted lattices as input, instead of sequences. A LATTICERNN can encode the completeExpand
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A Word Reordering Model for Improved Machine Translation
Preordering of source side sentences has proved to be useful in improving statistical machine translation. Most work has used a parser in the source language along with rules to map the sourceExpand
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Parametric Amplification and Wavelength Conversion of Single- and Dual-Polarization DQPSK Signals
We demonstrate system experiments for polarization-independent parametric amplification and wavelength conversion of single-channel differential quadrature phase-shift keying (DQPSK) signals up toExpand
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Neural network language models for low resource languages
For resource rich languages, recent works have shown Neural Network based Language Models (NNLMs) to be an effective modeling technique for Automatic Speech Recognition, out performing standardExpand
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Semi-supervised training in low-resource ASR and KWS
In particular for “low resource” Keyword Search (KWS) and Speech-to-Text (STT) tasks, more untranscribed test data may be available than training data. Several approaches have been proposed to makeExpand
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Using web text to improve keyword spotting in speech
For low resource languages, collecting sufficient training data to build acoustic and language models is time consuming and often expensive. But large amounts of text data, such as online newspapers,Expand
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Scalable Language Model Adaptation for Spoken Dialogue Systems
Language models (LM) for interactive speech recognition systems are trained on large amounts of data and the model parameters are optimized on past user data. New application intents and interactionExpand
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Clause-Based Reordering Constraints to Improve Statistical Machine Translation
We demonstrate that statistical machine translation (SMT) can be improved substantially by imposing clause-based reordering constraints during decoding. Our analysis of clause-wise translation ofExpand
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Contextual Language Model Adaptation for Conversational Agents
Statistical language models (LM) play a key role in Automatic Speech Recognition (ASR) systems used by conversational agents. These ASR systems should provide a high accuracy under a variety ofExpand
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Handling verb phrase morphology in highly inflected Indian languages for Machine Translation
The phrase based systems for machine translation are limited by the phrases that they see during the training. For highly inflected languages, it is uncommon to see all the forms of a word in theExpand
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