Title :
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
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;
Conference_Titel :
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
Conference_Location :
Dallas, TX
Print_ISBN :
978-1-4244-4295-9
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2010.5494959
