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Adam Chýlek

2 accepted papers

2016

A study of different weighting schemes for spoken language understanding based on convolutional neural networks

ICASSP 2016accepted

This paper describes the development of a stateless spoken spoken language understanding (SLU) module based on artificial neural networks that is able to deal with the uncertainty of the automatic speech recognition (ASR) output. The work builds upon the concept of weighted neurons introduced by the…

Cited by 0SourceScholar
2015

Word-semantic lattices for spoken language understanding

ICASSP 2015accepted

The paper presents a method for converting word-based automatic speech recognition (ASR) lattices into word-semantic (W-SE) lattices that contain original words together with a partial semantic information - so-called semantic entities. Semantic entity detection algorithm generates semantic entities…

Cited by 0SourceScholar