为虚拟助手建模口语信息查询：开放问题、挑战与机遇
Modeling Spoken Information Queries for Virtual Assistants: Open Problems, Challenges and Opportunities
AI总结：
本文探讨虚拟助手口语信息查询建模的开放问题与挑战，指出查询领域分类、知识图谱、用户交互数据和个性化可提升语音识别准确性。
摘要：
虚拟助手正成为日益重要的语音驱动信息检索平台，可协助用户完成各类任务。我们讨论了为虚拟助手建模口语信息查询所涉及的开放问题与挑战，并列出可应用信息检索方法和研究来提升虚拟助手语音识别质量的机遇。我们阐述了查询领域分类、知识图谱与用户交互数据，以及查询个性化如何有助于提升口语信息领域查询的准确识别。最后，我们还简要概述了当前语音识别中的问题与挑战。
英文摘要：
Virtual assistants are becoming increasingly important speech-driven Information Retrieval platforms that assist users with various tasks. We discuss open problems and challenges with respect to modeling spoken information queries for virtual assistants, and list opportunities where Information Retrieval methods and research can be applied to improve the quality of virtual assistant speech recognition. We discuss how query domain classification, knowledge graphs and user interaction data, and query personalization can be helpful to improve the accurate recognition of spoken information domain queries. Finally, we also provide a brief overview of current problems and challenges in speech recognition.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
