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Keyword: Utterance
How Effective is Using Lip Movement for Japanese Utterance Training
Lip movements have long been the subject of research. There are many methods of lip movement recognition, such as the calculation of the amount of movement compared to a matching face pattern. In a previous study, we investigated utterance recognition based on the power spectrum by focusing on lip movements, which is one aspect of…
Read More Extending the Classifier Algorithms in Machine Learning to Improve the Performance in Spoken Language Understanding Systems Under Deficient Training Data
One of the open domain challenges for Spoken Dialogue System (SDS) is to maintain a natural conversation for rarely visited domain i.e. domain with fewer data. Spoken Language Understanding (SLU) is a component of SDS that converts user utterance into a semantic form that a computer can understand. If we scale SDS open domain challenge…
Read More Retrieving Dialogue History in Deep Neural Networks for Spoken Language Understanding
In this paper, we propose a revised version of the semantic decoder for multi-label classification task in the spoken language understanding (SLU) pilot task of the Dialog State Tracking Challenge 5 (DSTC5). Our model concatenates two deep neural networks – a Convolutional Neural Network (CNN) and a Recurrent Neural Networks (RNN) – for detecting semantic…
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