Skip to search formSkip to main contentSkip to account menu

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… 
Wikipedia (opens in a new tab)

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2017
Highly Cited
2017
The environmental robustness of DNN-based acoustic models can be significantly improved by using multi-condition training data… 
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… 
Highly Cited
2015
Highly Cited
2015
Recurrent neural network architectures have been shown to efficiently model long term temporal dependencies between acoustic… 
Highly Cited
2015
Highly Cited
2015
Data augmentation is a common strategy adopted to increase the quantity of training data, avoid overfitting and improve… 
Highly Cited
2013
Highly Cited
2013
Recently, pre-trained deep neural networks (DNNs) have outperformed traditional acoustic models based on Gaussian mixture models… 
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… 
Highly Cited
2013
Highly Cited
2013
While Deep Neural Networks (DNNs) have achieved tremendous success for large vocabulary continuous speech recognition (LVCSR… 
Review
2012
Review
2012
Most current speech recognition systems use hidden Markov models (HMMs) to deal with the temporal variability of speech and… 
Review
2007
Review
2007
  • M. GalesS. Young
  • Foundations and Trends® in Signal Processing
  • 2007
  • Corpus ID: 51039442
Hidden Markov Models (HMMs) provide a simple and effective framework for modelling time-varying spectral vector sequences. As a… 
Highly Cited
2000
Highly Cited
2000
Abstract We describe a statistical approach for modeling dialogue acts in conversational speech, i.e., speech-act-like units such…