Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11889/8531
Title: An optimization based approach for solving spoken CALL shared task
Authors: Ateeq, Mohammad 
Hanani, Abualsoud 
Qaroush, Aziz 
Keywords: human-computer interaction;Automatic speech recognition;Signal processing;Contrastive linguistics;Computer simulation;Linguistic assessment
Issue Date: 2018
Publisher: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Abstract: In this paper, we are describing our developed systems for the 2018 SLaTE CALL Shared Task on grammatical and linguistic assessment of English spoken by German-speaking Swiss teenagers. The English spoken response is converted to text using baseline English DNN-HMM ASR trained on the shared task training data and another two commercial ASRs (Google and Microsoft Bing). The produced transcription is assessed in terms of language and meaning errors. In this work, we focused on the text-processing component. Grammatical errors are detected using English grammar checker, part of speech analysis and extracting incorrect bi-grams from grammatically incorrect responses. Errors related to the meaning are detected using novel approaches which measure the similarity between the given response and stored set of reference responses. The outputs of several systems have been fused together into one overall system, where the fusion weights and parameters are tuned using genetic algorithm. The best result on the 2018 shared task test dataset is D-score of 14.41, which was achieved by the fused system and the optimized set of incorrect bi-grams.
URI: http://hdl.handle.net/20.500.11889/8531
DOI: 10.21437/Interspeech.2018-1328
Appears in Collections:Fulltext Publications

Files in This Item:
File Description SizeFormat
An optimization based approach for solving spoken CALL shared task.pdf277.24 kBAdobe PDFView/Open
Show full item record

Page view(s)

15
checked on Jun 18, 2024

Download(s)

8
checked on Jun 18, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.