Character-based units for Unlimited Vocabulary Continuous Speech Recognition

We study character-based language models in the state-of-the-art speech recognition framework. This approach has advantages over both word-based systems and so-called end-to-end ASR systems that do not have separate acoustic and language models. We describe the necessary modifications needed to build an effective character-based ASR system using the Kaldi toolkit and evaluate the models based on words, statistical morphs, and characters for both Finnish and Arabic. The morph-based models yield the best recognition results for both well-resourced and lower-resourced tasks, but the character-based models are close to their performance in the lower-resource tasks, outperforming the word-based models. Character-based models are especially good at predicting novel word forms that were not seen in the training data. Using character-based neural network language models is both computationally efficient and provides a larger gain compared to the morph and word-based systems.

DOI

10.1109/ASRU.2017.8268929

Citation

Smit, P, Gangireddy, S, Enarvi, S, Virpioja, S & Kurimo, M 2018, Character-based units for Unlimited Vocabulary Continuous Speech Recognition. in Automatic Speech Recognition and Understanding (ASRU), IEEE Workshop on. IEEE, pp. 149-154, IEEE Automatic Speech Recognition and Understanding Workshop, Okinawa, Japan, 16/12/2017. https://doi.org/10.1109/ASRU.2017.8268929

Permanent link to this item

https://urn.fi/URN:NBN:fi:aalto-201802091465

Collections

[article-cris] Sähkötekniikan korkeakoulu / ELEC

Show all metadata

Character-based units for Unlimited Vocabulary Continuous Speech Recognition

Access rights

URL

Journal Title

Journal ISSN

Volume Title

Authors

Date

Department

Major/Subject

Mcode

Degree programme

Language

Pages

Series

Abstract

Description

Keywords

Other note

DOI

Citation

Permanent link to this item

Collections