部署可用于大规模使用的语音IVR系统

Chitralekha Bhat, B. Mithun, Vikram Saxena, Vrushali Kulkarni, Sunil Kumar Kopparapu
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引用次数: 12

摘要

交互式语音应答(Interactive Voice Response, IVR)技术使客户服务24x7且具有成本效益,已被大多数面向客户的企业所采用。虽然有效,但ivr需要使用触摸音电话输入,限制了可以输入的信息类型。出于这个原因,客户通常选择直接与人工座席交谈,从而否定了部署IVR的成本效益。在像印度这样的多语言国家,与人类座席交谈的需求更为深刻,此外,座席必须用客户的语言说话,这使得它无法扩展。基于语音技术的IVR解决方案不仅具有传统IVR系统的所有优点,而且还解决了配置为多语言工作时的可扩展性问题。为了使一个可用的语音IVR成为一个完整而强大的解决方案,需要处理几个方面,以维持准确服务客户的核心目标。在本文中,我们使用语音支持的铁路查询系统(SERES),该系统旨在提供牢记印度场景的铁路信息,作为案例研究,以确定需要解决的问题,以启用可用的基于语音的IVR解决方案。考虑的方面有a)客户体验的交互设计b)现场试验策略c)系统性能监控和评估d)基础设施规模以满足预期的呼叫量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deploying usable speech enabled IVR systems for mass use
Interactive Voice Response (IVR) technology makes customer service 24 × 7 and cost effective and has been used by most customer facing enterprises. While effective, IVRs requires inputs to be keyed in using a touch tone phone, constraining the type of information that can be input. For this reason customers in general choose to speak with a human agent directly, negating the cost effectiveness of deploying an IVR. The need to speak to a human agent is more profound in a multi linguistic country like India, where in addition the agent has to necessarily speak in the language of the customer, making it unscalable. Speech technology based IVR solutions not only have all the benefits of a conventional IVR system but in addition address the scalability issue when configured to work in multiple languages. In order to enable a usable Speech enabled IVR into a complete and robust solution, several aspects need to be handled to sustain the core objective of serving the customer accurately. In this paper, we use, Speech Enabled Railway Enquiry System (SERES) which has been designed to provide railway information keeping in mind the Indian scenario, as a case study to identify issues that need to be addressed to enable a usable speech based IVR solution. Aspects looked at are a) Interaction design for customer experience b) field trial strategy c) System performance monitoring and evaluation and d) Infrastructure sizing to cater to the expected call volumes.
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