Fraunhofer-Gesellschaft

Publica

Hier finden Sie wissenschaftliche Publikationen aus den Fraunhofer-Instituten.

Automatic topic detection for spoken input

 
: Soliman, Mohamed

:
Volltext urn:nbn:de:0011-n-4801006 (2.7 MByte PDF)
MD5 Fingerprint: 095a9a8f9b93fc7f24ac3761f20f0b06
Erstellt am: 11.1.2018


Aachen, 2017, 75 S.
Aachen, TH, Master Thesis, 2017
Englisch
Master Thesis, Elektronische Publikation
Fraunhofer IAIS ()

Abstract
In the Natural Language Understanding field, one of the important tasks is topic detection. Given the recent advancements in the field of deep learning, we explore the task of automatic topic detection for spoken input in the news domain. In this work, we study the effect of applying deep learning techniques such as Recurrent Neural Networks and Word Embeddings to the task of topic segmentation and topic detection given a spoken text stream. We also study the performance of the system given both written and spoken text using our novel approach for text segmentation.

: http://publica.fraunhofer.de/dokumente/N-480100.html