Paraphrase detection on SMS messages in automobiles

Author

Wu, Wei ; Ju, Yun-Cheng ; Li, Xiao ; Wang, Ye-Yi

Author_Institution

Univ. of Washington, Seattle, WA, USA

fYear

2010

fDate

14-19 March 2010

Firstpage

5326

Lastpage

5329

Abstract

Voice search technology has been successfully applied to help drivers reply SMS messages in automobiles, in which a predefined SMS message template set is searched with ASR hypotheses to form the reply candidate list. In order to efficiently organize the SMS message template set and improve the quality of the reply candidate list, we proposed to apply n-gram translation model and logistic regression to detect paraphrase SMS messages. Both of the proposed algorithms outperform the edit distance based paraphrase detection baseline, brining 40.9% and 50.5% EER reduction (relative), respectively.

Keywords

automobiles; electronic messaging; natural language processing; speech recognition; SMS message; automobiles; logistic regression; n gram translation model; paraphrase detection; voice search technology; Acoustic signal detection; Automatic speech recognition; Automobiles; Data mining; Degradation; Design methodology; Feature extraction; Logistics; Redundancy; Support vector machines; SMS message; logistic regression; n-gram; paraphrase detection; translation model;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on

Conference_Location

Dallas, TX

ISSN

1520-6149

Print_ISBN

978-1-4244-4295-9

Electronic_ISBN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2010.5494959

Filename

5494959