{"title":"阅读日常情绪数据库(REED):一套以音乐和语言表达情绪的视听记录","authors":"Jia Hoong Ong, Florence Yik Nam Leung, Fang Liu","doi":"10.1007/s10579-023-09698-5","DOIUrl":null,"url":null,"abstract":"<p>Most audio-visual (AV) emotion databases consist of clips that do not reflect real-life emotion processing (e.g., professional actors in bright studio-like environment), contain only spoken clips, and none have sung clips that express complex emotions. Here, we introduce a new AV database, the Reading Everyday Emotion Database (REED), which directly addresses those gaps. We recorded the faces of everyday adults with a diverse range of acting experience expressing 13 emotions—neutral, the six basic emotions (angry, disgusted, fearful, happy, sad, surprised), and six complex emotions (embarrassed, hopeful, jealous, proud, sarcastic, stressed)—in two auditory domains (spoken and sung) using everyday recording devices (e.g., laptops, mobile phones, etc.). The recordings were validated by an independent group of raters. We found that: intensity ratings of the recordings were positively associated with recognition accuracy; and the basic emotions, as well as the Neutral and Sarcastic emotions, were recognised more accurately than the other complex emotions. Emotion recognition accuracy also differed by utterance. Exploratory analysis revealed that recordings of those with drama experience were better recognised than those without. Overall, this database will benefit those who need AV clips with natural variations in both emotion expressions and recording environment.</p>","PeriodicalId":49927,"journal":{"name":"Language Resources and Evaluation","volume":"6 6","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Reading Everyday Emotion Database (REED): a set of audio-visual recordings of emotions in music and language\",\"authors\":\"Jia Hoong Ong, Florence Yik Nam Leung, Fang Liu\",\"doi\":\"10.1007/s10579-023-09698-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Most audio-visual (AV) emotion databases consist of clips that do not reflect real-life emotion processing (e.g., professional actors in bright studio-like environment), contain only spoken clips, and none have sung clips that express complex emotions. Here, we introduce a new AV database, the Reading Everyday Emotion Database (REED), which directly addresses those gaps. We recorded the faces of everyday adults with a diverse range of acting experience expressing 13 emotions—neutral, the six basic emotions (angry, disgusted, fearful, happy, sad, surprised), and six complex emotions (embarrassed, hopeful, jealous, proud, sarcastic, stressed)—in two auditory domains (spoken and sung) using everyday recording devices (e.g., laptops, mobile phones, etc.). The recordings were validated by an independent group of raters. We found that: intensity ratings of the recordings were positively associated with recognition accuracy; and the basic emotions, as well as the Neutral and Sarcastic emotions, were recognised more accurately than the other complex emotions. Emotion recognition accuracy also differed by utterance. Exploratory analysis revealed that recordings of those with drama experience were better recognised than those without. Overall, this database will benefit those who need AV clips with natural variations in both emotion expressions and recording environment.</p>\",\"PeriodicalId\":49927,\"journal\":{\"name\":\"Language Resources and Evaluation\",\"volume\":\"6 6\",\"pages\":\"\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2023-11-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Language Resources and Evaluation\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1007/s10579-023-09698-5\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Language Resources and Evaluation","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s10579-023-09698-5","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
The Reading Everyday Emotion Database (REED): a set of audio-visual recordings of emotions in music and language
Most audio-visual (AV) emotion databases consist of clips that do not reflect real-life emotion processing (e.g., professional actors in bright studio-like environment), contain only spoken clips, and none have sung clips that express complex emotions. Here, we introduce a new AV database, the Reading Everyday Emotion Database (REED), which directly addresses those gaps. We recorded the faces of everyday adults with a diverse range of acting experience expressing 13 emotions—neutral, the six basic emotions (angry, disgusted, fearful, happy, sad, surprised), and six complex emotions (embarrassed, hopeful, jealous, proud, sarcastic, stressed)—in two auditory domains (spoken and sung) using everyday recording devices (e.g., laptops, mobile phones, etc.). The recordings were validated by an independent group of raters. We found that: intensity ratings of the recordings were positively associated with recognition accuracy; and the basic emotions, as well as the Neutral and Sarcastic emotions, were recognised more accurately than the other complex emotions. Emotion recognition accuracy also differed by utterance. Exploratory analysis revealed that recordings of those with drama experience were better recognised than those without. Overall, this database will benefit those who need AV clips with natural variations in both emotion expressions and recording environment.
期刊介绍:
Language Resources and Evaluation is the first publication devoted to the acquisition, creation, annotation, and use of language resources, together with methods for evaluation of resources, technologies, and applications.
Language resources include language data and descriptions in machine readable form used to assist and augment language processing applications, such as written or spoken corpora and lexica, multimodal resources, grammars, terminology or domain specific databases and dictionaries, ontologies, multimedia databases, etc., as well as basic software tools for their acquisition, preparation, annotation, management, customization, and use.
Evaluation of language resources concerns assessing the state-of-the-art for a given technology, comparing different approaches to a given problem, assessing the availability of resources and technologies for a given application, benchmarking, and assessing system usability and user satisfaction.