论文标题
印地语和英语演讲中的侵略：声学相关和自动身份
Aggression in Hindi and English Speech: Acoustic Correlates and Automatic Identification
论文作者
论文摘要
在本文中，我们将介绍印地语中对政治话语的声学分析的结果，并讨论印地语和英语发言人经常使用的激进言论的传统声学特征。该研究基于一个超过10个小时的政治话语的语料库，其中包括有关新闻渠道和政治演讲的辩论。使用这项研究，我们开发了两个自动分类系统，用于仅基于声学模型来识别英语和印地语语音的侵略性。使用50小时的注释语音和英语分类器培训的印地语分类器，使用40小时的注释语音进行了培训，分别获得了73％以上和66％的可观精度。在本文中，我们讨论了该注释数据集的开发，即开发分类器并讨论其犯错误的实验。
In the present paper, we will present the results of an acoustic analysis of political discourse in Hindi and discuss some of the conventionalised acoustic features of aggressive speech regularly employed by the speakers of Hindi and English. The study is based on a corpus of slightly over 10 hours of political discourse and includes debates on news channel and political speeches. Using this study, we develop two automatic classification systems for identifying aggression in English and Hindi speech, based solely on an acoustic model. The Hindi classifier, trained using 50 hours of annotated speech, and English classifier, trained using 40 hours of annotated speech, achieve a respectable accuracy of over 73% and 66% respectively. In this paper, we discuss the development of this annotated dataset, the experiments for developing the classifier and discuss the errors that it makes.
