话务员服务自动化:语音识别技术的成功应用

W. E. Longenbaker, R. J. Perdue, S. M. Salchenberger
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引用次数: 5

摘要

[b]本文描述了语音识别技术在基于电话网络的系统中成功部署的挑战和设计决策,该系统提供自动操作员服务。简要回顾了在本工作之前在运营商自动化方面的相关进展,并概述了将自动语音识别(ASR)引入自动替代计费服务(AABS)的要求。重点介绍了支持技术的进步,包括单词识别和入侵,并讨论了应用程序的总体部署策略。描述了使用独立于说话人的全词模型的计费类型和计费接受识别任务,并报告了现场结果。总结了数据收集和模型改进的“自举”方法。接下来,描述了使用连接数字ASR的账单细节识别试验的当前结果。这些试验正在进行中,涉及识别10位数的电话号码和14位数的电话卡号码。AABS-ASR服务已经在美国全面部署,仅AT&T一个月就能处理超过5000万个电话。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automation of operator services: a successful application of speech recognition technology
[BThe challenges and design decisions associated with the successful deployment of speech recognition technology in a telephone network-based system providing automated operator services are described. The relevant advances in operator automation that had preceded the present work are briefly reviewed, and the requirements for the introduction of automated speech recognition (ASR) into the automated alternate billing service (AABS) are outlined. The enabling technology advances, including word spotting and barge-in, are highlighted, and the overall deployment strategy for the application is discussed. The billing type and billing acceptance recognition tasks, using speaker-independent whole word models, are described and field results reported. The "bootstrapping" approach to data collection and model improvements is summarized. Next, the current results of the billing detail recognition trials using connected digit ASR are described. These trials are ongoing and involve the recognition of 10-digit telephone numbers and 14-digit calling card numbers. The AABS-ASR service has been fully deployed across the United States and handles over 50 million calls a month for AT&T alone.<>
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