Recent Advances in End-to-End Spoken Language Understanding
September 29, 2019 ยท The Cartographer ยท ๐ International Conference on Statistical Language and Speech Processing
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"Title-pattern auto-detect: Recent Advances in End-to-End Spoken Language Understanding"
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Authors
Natalia Tomashenko, Antoine Caubriere, Yannick Esteve, Antoine Laurent, Emmanuel Morin
arXiv ID
1909.13332
Category
cs.CL: Computation & Language
Cross-listed
eess.AS
Citations
29
Venue
International Conference on Statistical Language and Speech Processing
Last Checked
2 days ago
Abstract
This work investigates spoken language understanding (SLU) systems in the scenario when the semantic information is extracted directly from the speech signal by means of a single end-to-end neural network model. Two SLU tasks are considered: named entity recognition (NER) and semantic slot filling (SF). For these tasks, in order to improve the model performance, we explore various techniques including speaker adaptation, a modification of the connectionist temporal classification (CTC) training criterion, and sequential pretraining.
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