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The development of the Athens Emotional States Inventory (AESI): collection, validation and automatic processing of emotionally loaded sentences

机译:雅典情绪状态量表(AESI)的开发:收集,验证和自动处理情绪化的句子

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Objectives. The development of ecologically valid procedures for collecting reliable and unbiased emotional data towards computer interfaces with social and affective intelligence targeting patients with mental disorders. Methods. Following its development, presented with, the Athens Emotional States Inventory (AESI) proposes the design, recording and validation of an audiovisual database for five emotional states: anger, fear, joy, sadness and neutral. The items of the AESI consist of sentences each having content indicative of the corresponding emotion. Emotional content was assessed through a survey of 40 young participants with a questionnaire following the Latin square design. The emotional sentences that were correctly identified by 85% of the participants were recorded in a soundproof room with microphones and cameras. A preliminary validation of AESI is performed through automatic emotion recognition experiments from speech. Results. The resulting database contains 696 recorded utterances in Greek language by 20 native speakers and has a total duration of approximately 28 min. Speech classification results yield accuracy up to 75.15% for automatically recognizing the emotions in AESI. Conclusions. These results indicate the usefulness of our approach for collecting emotional data with reliable content, balanced across classes and with reduced environmental variability.
机译:目标。开发生态有效的程序,以收集针对精神疾病患者的社交和情感智能的计算机接口的可靠且公正的情感数据。方法。伴随着它的发展,雅典情绪状态清单(AESI)提出了针对五个情绪状态的设计,记录和验证的视听数据库:愤怒,恐惧,喜悦,悲伤和中立。 AESI的项目由句子组成,每个句子都具有指示相应情感的内容。根据拉丁方设计,通过对40名年轻参与者的问卷调查,评估了他们的情感内容。 85%的参与者正确识别出的情感句子记录在带有麦克风和摄像头的隔音室中。 AESI的初步验证是通过语音的自动情感识别实验进行的。结果。最终的数据库包含20位以母语为母语的人录制的696则希腊语语音,总时长约为28分钟。语音分类结果产生的准确度高达75.15%,可自动识别AESI中的情绪。结论。这些结果表明,我们的方法对于收集内容可靠,跨课程平衡且环境变异性降低的情感数据很有用。

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