Speech analytics

Known as: LVCSR 
Speech analytics is the process of analyzing recorded calls to gather customer information to improve communication and future interaction. The… (More)
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Papers overview

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Highly Cited
2016
Highly Cited
2016
Many state-of-the-art Large Vocabulary Continuous Speech Recognition (LVCSR) Systems are hybrids of neural networks and Hidden… (More)
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Highly Cited
2015
Highly Cited
2015
Recurrent neural network architectures have been shown to efficiently model long term temporal dependencies between acoustic… (More)
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Highly Cited
2013
Highly Cited
2013
Convolutional Neural Networks (CNNs) are an alternative type of neural network that can be used to reduce spectral variations and… (More)
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Highly Cited
2013
Highly Cited
2013
While Deep Neural Networks (DNNs) have achieved tremendous success for large vocabulary continuous speech recognition (LVCSR… (More)
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Highly Cited
2011
Highly Cited
2011
To date, there has been limited work in applying Deep Belief Networks (DBNs) for acoustic modeling in LVCSR tasks, with past work… (More)
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Highly Cited
2010
Highly Cited
2010
Large vocabulary speech recognition with multiple speakers and variable channel conditions is a challenging task. State-of-the… (More)
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Highly Cited
2007
Highly Cited
2007
In recent years, probabilistic features became an integral part of state-of-the-are LVCSR systems. In this work, we are exploring… (More)
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2005
2005
This paper describes an adaptive system and infrastructure for Speech Analytics, based on the UIMA framework and consisting of a… (More)
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Highly Cited
2001
Highly Cited
2001
Julius is a high-performance, two-pass LVCSR decoder for researchers and developers. Based on word 3-gram and context-dependent… (More)
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Highly Cited
2001
Highly Cited
2001
With the distribution of speech technology products all over the world, the portability to new target languages becomes a… (More)
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