@inproceedings{0f355fbc80704fdd929571347eaa27f6,
title = "Case based reasoning solution to the problem of sustained learning in keyword spotting",
abstract = "In some practical keyword spotting applications, users or service providers are willing to provide spotting-result feedback to help improve system performance. To do so, they require a keyword spotting technique with a sustained learning ability. This paper presents a new Chinese keyword spotting method based on a case based reasoning framework. Two level keyword case representations are adopted based on a set of symbols that are discriminative both in acoustic feature vector space and in semantic space. Then case bases are indexed with a tree structure and searched for test speech based on an elastic matching strategy. Finally, the feedback is used to adjust the statistics attached to the cases or to append new cases. Two experiments were conducted to compare our approach with a syllable lattice based method and to test the sustained learning ability.",
keywords = "Keyword spotting, acoustic symbol clustering, case based reasoning, sustained learning",
author = "Tieran Zheng and Jiqing Han and Guibin Zheng and Shiwen Deng",
year = "2013",
month = oct,
day = "18",
doi = "10.1109/ICASSP.2013.6639338",
language = "英语",
isbn = "9781479903566",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
pages = "8570--8574",
booktitle = "2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings",
note = "2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 ; Conference date: 26-05-2013 Through 31-05-2013",
}