Predictive text entry using syntax and semantics
Ganslandt, Sebastian ; Jörwall, Jakob and Nugues, Pierre LU
(2009)
p.37-48
- Abstract
- Most cellular telephones use numeric keypads, where texting is supported by dictionaries and frequency models. Given a key sequence, the entry system recognizes the matching words and proposes a rank-ordered list of candidates. The ranking quality is instrumental to an effective entry.
This paper describes a new method to enhance entry that combines syntax and language models. We first investigate components to improve the ranking step: language models and semantic relatedness. We then introduce a novel syntactic model to capture the word context, optimize ranking, and then reduce the number of keystrokes per character (KSPC) needed to write a text. We finally combine this model with the other components and we discuss... (More) - Most cellular telephones use numeric keypads, where texting is supported by dictionaries and frequency models. Given a key sequence, the entry system recognizes the matching words and proposes a rank-ordered list of candidates. The ranking quality is instrumental to an effective entry.
This paper describes a new method to enhance entry that combines syntax and language models. We first investigate components to improve the ranking step: language models and semantic relatedness. We then introduce a novel syntactic model to capture the word context, optimize ranking, and then reduce the number of keystrokes per character (KSPC) needed to write a text. We finally combine this model with the other components and we discuss the results.
We show that our syntax-based model reaches an error reduction in KSPC of 12.4% on a Swedish corpus over a baseline using word frequencies. We also show that bigrams are superior to all the other models. However, bigrams have a memory footprint that is unfit for most devices. Nonetheless, bigrams can be further improved by the addition of syntactic models with an error reduction that reaches 29.4%. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1668773
- author
- Ganslandt, Sebastian
; Jörwall, Jakob
and Nugues, Pierre
LU
- organization
- publishing date
- 2009
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Proceedings of the 11th International Conference on Parsing Technologies (IWPT '09)
- pages
- 37 - 48
- external identifiers
-
- scopus:85041439950
- language
- English
- LU publication?
- yes
- id
- 050b698b-73c4-4859-a211-abe6933095e2 (old id 1668773)
- alternative location
- http://dl.acm.org/citation.cfm?id=1697244
- date added to LUP
- 2016-04-04 13:59:04
- date last changed
- 2025-10-14 11:48:12
@inproceedings{050b698b-73c4-4859-a211-abe6933095e2,
abstract = {{Most cellular telephones use numeric keypads, where texting is supported by dictionaries and frequency models. Given a key sequence, the entry system recognizes the matching words and proposes a rank-ordered list of candidates. The ranking quality is instrumental to an effective entry.<br/><br>
<br/><br>
This paper describes a new method to enhance entry that combines syntax and language models. We first investigate components to improve the ranking step: language models and semantic relatedness. We then introduce a novel syntactic model to capture the word context, optimize ranking, and then reduce the number of keystrokes per character (KSPC) needed to write a text. We finally combine this model with the other components and we discuss the results.<br/><br>
<br/><br>
We show that our syntax-based model reaches an error reduction in KSPC of 12.4% on a Swedish corpus over a baseline using word frequencies. We also show that bigrams are superior to all the other models. However, bigrams have a memory footprint that is unfit for most devices. Nonetheless, bigrams can be further improved by the addition of syntactic models with an error reduction that reaches 29.4%.}},
author = {{Ganslandt, Sebastian and Jörwall, Jakob and Nugues, Pierre}},
booktitle = {{Proceedings of the 11th International Conference on Parsing Technologies (IWPT '09)}},
language = {{eng}},
pages = {{37--48}},
title = {{Predictive text entry using syntax and semantics}},
url = {{http://dl.acm.org/citation.cfm?id=1697244}},
year = {{2009}},
}