Speech Emotion Recognition Adapted to Multimodal Semantic Repositories
Speech Emotion Recognition Adapted to Multimodal Semantic Repositories
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DOI：
10.1109/smap.2018.8501881
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发表时间：
2018-09
期刊：
影响因子：
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通讯作者：
N. Vryzas;Lazaros Vrysis;Rigas Kotsakis;Charalampos A. Dimoulas
中科院分区：
文献类型：
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作者：
N. Vryzas;Lazaros Vrysis;Rigas Kotsakis;Charalampos A. Dimoulas
言语情绪是言语交际的一个重要的副语言因素，它无疑涉及到高度的主观性，而隐含的情绪状态并没有具体的建模。具体来说，情感表达在不同的语言和不同的人之间有很大的差异。目前的工作重点是研究情绪状态的识别潜力，以适应/个性化的方法，旨在创建一个有效的多模态语音情绪识别服务。在此背景下，我们建立了一个情感言语基础真值数据库，其中包含了特定说话者在五种基本情绪中的语义/情感“负载”话语。在进行的实验中，实现了几种分类算法，并与广义/增强多说话人情绪语音数据库的结果进行了比较。此外，基于音频的应用程序设计用于实时情绪识别，同时利用语音记录工具结合摄像头和语音转文本模块。每个语音的音频、视频和文本文件都通过用户友好和功能强大的图形用户界面进行标记和存储，以便后续扩大个性化数据库。
Speech emotion is an important paralinguistic element of speech communication, which undoubtedly involves high level of subjectivity, without concrete modeling of the implicated emotional states. Specifically, sentimental expression varies in great proportions among different spoken languages and persons. The current work is focused on the investigation of emotional states discrimination potentials, in an adaptive/personalized approach, aiming at the creation of an effective multimodal speech emotion recognition service. In this context, an emotional speech ground truth database is formulated, containing semantically/ emotionally "loaded" utterances of a certain speaker in five basic sentiments. In the conducted experiments several classification algorithms are implemented and compared to the results of a generalized/ augmented multi-speaker emotional speech database. Furthermore, an audio-based application is designed for real time sentiment identification, while utilizing speech recording tools combined with camera and a Speech-to-Text modules. The audio, video and text files for every spoken utterance are labeled and stored via a user-friendly and functional GUI, for the subsequent augmentation of the personalized database.