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Spoken document retrieval from call-center conversations

Published: 06 August 2006 Publication History

Abstract

We are interested in retrieving information from conversational speech corpora, such as call-center data. This data comprises spontaneous speech conversations with low recording quality, which makes automatic speech recognition (ASR) a highly difficult task. For typical call-center data, even state-of-the-art large vocabulary continuous speech recognition systems produce a transcript with word error rate of 30% or higher. In addition to the output transcript, advanced systems provide word confusion networks (WCNs), a compact representation of word lattices associating each word hypothesis with its posterior probability. Our work exploits the information provided by WCNs in order to improve retrieval performance. In this paper, we show that the mean average precision (MAP) is improved using WCNs compared to the raw word transcripts. Finally, we analyze the effect of increasing ASR word error rate on search effectiveness. We show that MAP is still reasonable even under extremely high error rate.

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    cover image ACM Conferences
    SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
    August 2006
    768 pages
    ISBN:1595933697
    DOI:10.1145/1148170
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 06 August 2006

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    • (2021)Spoken Conversational Context Improves Query Auto-completion in Web SearchACM Transactions on Information Systems10.1145/344787539:3(1-32)Online publication date: 5-May-2021
    • (2021)Hierarchical Knowledge Distillation for Dialogue Sequence Labeling2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)10.1109/ASRU51503.2021.9687959(433-440)Online publication date: 13-Dec-2021
    • (2019)Towards Identifying Impacted Users in Cellular ServicesProceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3292500.3330711(3029-3039)Online publication date: 25-Jul-2019
    • (2018)Online Call Scene Segmentation of Contact Center Dialogues based on Role Aware Hierarchical LSTM-RNNs2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)10.23919/APSIPA.2018.8659521(811-815)Online publication date: Nov-2018
    • (2018)Building Test Speech Dataset on Russian Language for Spoken Document Retrieval Task2018 IEEE East-West Design & Test Symposium (EWDTS)10.1109/EWDTS.2018.8524598(1-4)Online publication date: Sep-2018
    • (2017)Pruning Strategies for Partial Search in Spoken Term DetectionProceedings of the 8th International Symposium on Information and Communication Technology10.1145/3155133.3155164(114-119)Online publication date: 7-Dec-2017
    • (2016)Estimating Speech Recognition Accuracy Based on Error Type ClassificationIEEE/ACM Transactions on Audio, Speech and Language Processing10.1109/TASLP.2016.260359924:12(2400-2413)Online publication date: 1-Dec-2016
    • (2016)Keyword search using query expansion for graph-based rescoring of hypothesized detections2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2016.7472836(6035-6039)Online publication date: Mar-2016
    • (2015)Spoken content retrievalIEEE/ACM Transactions on Audio, Speech and Language Processing10.1109/TASLP.2015.243854323:9(1389-1420)Online publication date: 1-Sep-2015
    • (2015)ConSentKnowledge-Based Systems10.1016/j.knosys.2015.04.00984:C(162-178)Online publication date: 1-Aug-2015
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