Mokaram, S. and Moore, R.K. (2015) Speech-Based Location Estimation of First Responders in a Simulated Search and Rescue Scenario. In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH. 16th Annual Conference of the International Speech Communication Association, 06-10 Sep 2015, Dresden, Germany. ISCA (International Speech Communication Association) , 2734 - 2738 (5).
Abstract
In our research, we explore possible solutions for extracting valuable information about first responders’ (FR) location from speech communication channels during crisis response. Fine-grained identification of fundamental units of meaning (e. g. sentences, named entities and dialogue acts) is sensitive to high error rate in automatic transcriptions of noisy speech. However, looking from a topic-based perspective and utilizing text vectorization techniques such as Latent Dirichlet Allocation (LDA) make this more robust to such errors. In this paper, the location estimation problem is framed as a topic segmentation task on FRs’ spoken reports about their observations and actions. Identifying the changes in the content of a report over time is an indication that the speaker has moved from one particular location to another. This provides an estimation about the location of the speaker. A goal-oriented human/human conversational speech corpus was collected based on an abstract communication model between FR and task leader during a search process in a simulation environment. Results show the effectiveness of a topic-based approach and especially low sensitivity of the LDA-based method to the highly imperfect automatic transcriptions.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015 ISCA. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | spoken language understanding; speech recognition; topic segmentation; Latent Dirichlet Allocation (LDA); human/human conversation |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 04 Mar 2016 10:17 |
Last Modified: | 19 Dec 2022 13:32 |
Published Version: | http://www.isca-speech.org/archive/interspeech_201... |
Status: | Published |
Publisher: | ISCA (International Speech Communication Association) |
Refereed: | Yes |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:92309 |