Learning about Voice Search for Spoken Dialogue Systems
Learning about Voice Search for Spoken Dialogue Systems
复制标题
了解口语对话系统的语音搜索
DOI：
--
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
Pravin Bhutada
中科院分区：
文献类型：
--
作者：
R. Passonneau;Susan L. Epstein;Tiziana Ligorio;Joshua B. Gordon;Pravin Bhutada
在一个有多个向导对象的绿野仙踪实验中，每个向导都查看了自动语音识别(ASR)结果，以了解其解释对任务成功至关重要的话语：从图书馆数据库按标题请求图书。为了避免不理解，向导直接使用ASR假设(语音搜索)查询应用程序数据库。为了了解如何避免误解，我们调查了巫师如何处理语音搜索结果中的不确定性。向导非常成功地从包括匹配的查询结果中选择了正确的标题。最成功的向导还可以判断查询结果何时不包含所请求的标题。我们学习的最佳巫师行为模型将巫师可用的功能与一些不适用的功能结合在一起，例如识别置信度和声学模型分数。
In a Wizard-of-Oz experiment with multiple wizard subjects, each wizard viewed automated speech recognition (ASR) results for utterances whose interpretation is critical to task success: requests for books by title from a library database. To avoid non-understandings, the wizard directly queried the application database with the ASR hypothesis (voice search). To learn how to avoid misunderstandings, we investigated how wizards dealt with uncertainty in voice search results. Wizards were quite successful at selecting the correct title from query results that included a match. The most successful wizard could also tell when the query results did not contain the requested title. Our learned models of the best wizard's behavior combine features available to wizards with some that are not, such as recognition confidence and acoustic model scores.
口语对话系统数据库搜索任务中基于对话模型的语境约束
DOI：
--
发表时间：
2005
期刊：
Proceedings of the Nineth European Conference on Speech Communication and Technology (Interspeech-2005)
影响因子：
--
作者：
T.Kondoh;M.Bannai;H.Nishino;K.Torii;Kazunori Komatani
通讯作者：
Kazunori Komatani