The RWTH Aachen LVCSR system for IWSLT-2016 German Skype conversation recognition task

Wilfried Michel, Zoltán Tüske, M. Ali Basha Shaik, Ralf Schlüter, Hermann Ney


Abstract
In this paper the RWTH large vocabulary continuous speech recognition (LVCSR) systems developed for the IWSLT-2016 evaluation campaign are described. This evaluation campaign focuses on transcribing spontaneous speech from Skype recordings. State-of-the-art bidirectional long short-term memory (LSTM) and deep, multilingually boosted feed-forward neural network (FFNN) acoustic models are trained an narrow and broadband features. An open vocabulary approach using subword units is also considered. LSTM and count-based full word and hybrid backoff language modeling methods are used to model the morphological richness of the German language. All these approaches are combined using confusion network combination (CNC) to yield a competitive WER.
Anthology ID:
2016.iwslt-1.17
Volume:
Proceedings of the 13th International Conference on Spoken Language Translation
Month:
December 8-9
Year:
2016
Address:
Seattle, Washington D.C
Editors:
Mauro Cettolo, Jan Niehues, Sebastian Stüker, Luisa Bentivogli, Rolando Cattoni, Marcello Federico
Venue:
IWSLT
SIG:
SIGSLT
Publisher:
International Workshop on Spoken Language Translation
Note:
Pages:
Language:
URL:
https://aclanthology.org/2016.iwslt-1.17
DOI:
Bibkey:
Cite (ACL):
Wilfried Michel, Zoltán Tüske, M. Ali Basha Shaik, Ralf Schlüter, and Hermann Ney. 2016. The RWTH Aachen LVCSR system for IWSLT-2016 German Skype conversation recognition task. In Proceedings of the 13th International Conference on Spoken Language Translation, Seattle, Washington D.C. International Workshop on Spoken Language Translation.
Cite (Informal):
The RWTH Aachen LVCSR system for IWSLT-2016 German Skype conversation recognition task (Michel et al., IWSLT 2016)
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PDF:
https://aclanthology.org/2016.iwslt-1.17.pdf