Empirical Studies of Everyday Professional, Domestic and Client-Service Communication for the Development of Voice Assistants in Russian

Tatiana Y. Sherstinova, Irina Petrova, O. Mineeva, Maria Fedosova
{"title":"Empirical Studies of Everyday Professional, Domestic and Client-Service Communication for the Development of Voice Assistants in Russian","authors":"Tatiana Y. Sherstinova, Irina Petrova, O. Mineeva, Maria Fedosova","doi":"10.23919/FRUCT56874.2022.9953821","DOIUrl":null,"url":null,"abstract":"Voice assistants are gradually becoming an increasingly common feature of our everyday life. However, the naturalness of communication provided by them usually leaves much to be desired. It may be caused by the fact that many chat-bots are trained on artificially created linguistic data sets and on fictional dialogues modeled by linguists on the basis of common phrasebooks or communication textbooks. As a result, the necessary pragmatic result can be achieved, but the feeling of “unnatural” communication of a voice assistant remains, which often reveals itself by the use of archaic phrases or remarks that are not quite suitable for the situation. This state of affairs seems to be improved by referring to real speech data―namely, to a representative volume of sound recordings of real speech communication. The paper discusses some approaches to the analysis of speech data from the sound corpus “One Day of Speech”, which is the most representative resource of Russian everyday spoken communication. The pragmatic structure of professional and everyday conversations is considered, as well as linguistic content of standard modules, such as Greeting and Farewell. As a practical recommendation, we can suggest increasing the variability of answers not due to the lexical diversity of phrases, but due to a more diverse intonation implementation for the most typical replicas in spoken Russian.","PeriodicalId":274664,"journal":{"name":"2022 32nd Conference of Open Innovations Association (FRUCT)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 32nd Conference of Open Innovations Association (FRUCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/FRUCT56874.2022.9953821","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Voice assistants are gradually becoming an increasingly common feature of our everyday life. However, the naturalness of communication provided by them usually leaves much to be desired. It may be caused by the fact that many chat-bots are trained on artificially created linguistic data sets and on fictional dialogues modeled by linguists on the basis of common phrasebooks or communication textbooks. As a result, the necessary pragmatic result can be achieved, but the feeling of “unnatural” communication of a voice assistant remains, which often reveals itself by the use of archaic phrases or remarks that are not quite suitable for the situation. This state of affairs seems to be improved by referring to real speech data―namely, to a representative volume of sound recordings of real speech communication. The paper discusses some approaches to the analysis of speech data from the sound corpus “One Day of Speech”, which is the most representative resource of Russian everyday spoken communication. The pragmatic structure of professional and everyday conversations is considered, as well as linguistic content of standard modules, such as Greeting and Farewell. As a practical recommendation, we can suggest increasing the variability of answers not due to the lexical diversity of phrases, but due to a more diverse intonation implementation for the most typical replicas in spoken Russian.
俄语语音助手发展的日常专业、家庭和客户服务沟通实证研究
语音助手正逐渐成为我们日常生活中越来越普遍的特征。然而,它们提供的自然交流通常还有很多需要改进的地方。这可能是由于许多聊天机器人是在人工创建的语言数据集上进行训练的,或者是在语言学家根据常用短语书或交流教科书模拟的虚构对话上进行训练的。因此,可以达到必要的语用效果,但语音助手的“不自然”交流的感觉仍然存在,这种感觉经常表现为使用不太适合当时情况的古老短语或言论。通过参考真实的语音数据,即真实语音交流的具有代表性的录音量,这种情况似乎得到了改善。本文探讨了俄语日常口语交际中最具代表性的语音语料库《一天讲话》语音数据的分析方法。专业和日常会话的语用结构,以及标准模块的语言内容,如问候和告别。作为一个实际的建议,我们可以建议增加答案的可变性,而不是由于短语的词汇多样性,而是由于在俄语口语中最典型的副本中使用更多样化的语调实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信