Document Type

Conference Proceeding

Publication Date


Published In

Proceedings Of The 2017 Conference On Empirical Methods In Natural Language Processing


Syllabification does not seem to improve word-level RNN language modeling quality when compared to character-based segmentation. However, our best syllable-aware language model, achieving performance comparable to the competitive character-aware model, has 18%-33% fewer parameters and is trained 1.2-2.2 times faster.

Published By

Association For Computational Linguistics

Conference Dates

September 7-11, 2017

Conference Location

Copenhagen, Denmark

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.


This work is freely available under a Creative Commons license.

Included in

Linguistics Commons