感觉:印尼语音数据集用于情绪分类
Anugrayani Bustamin1, Andi M Rizky1, Elly Warni1
1Informatics Department, Universitas Hasanuddin, Poros Malino Street Km 6, Gowa, South Sulawesi, Indonesia.
Data in brief
|December 17, 2024
概括
这项研究介绍了IndoWaveSentiment,这是用于识别语音情绪的新数据集. 它以印尼情感语音录音为特色,以推进情感分析和机器学习模型.
科学领域:
- 人工智能的人工智能
- 信号处理 信号处理
- 自然语言处理自然语言处理.
背景情况:
- 语音是人类沟通的主要媒介,比文字更快地传达情绪.
- 情感分析主要依赖于理解语言中的情感线索.
- 现有的数据集可能无法充分捕捉情感声调的细微差别.
研究的目的:
- 介绍IndoWaveSentiment,这是一个用于语音情感识别的新型数据集.
- 为开发和评估情绪分析模型提供资源.
- 支持人机交互和情感计算方面的研究.
主要方法:
- 收集了十位演员 (男性和女性) 在工作室的录音.
- 在五种情感类别中,以印尼语录的发言:中立,快乐,惊,厌恶和失望.
- 使用Audacity进行注释的音频数据,并使用基于问卷的采样技术进行验证.
主要成果:
- 成功创建了情感语音录音的分类数据集.
- 数据集包括每位演员每种情绪的多个记录,确保数据多样性.
- 手动注释和验证确保数据集的质量和可靠性.
结论:
- 对于信号处理和人工智能研究人员来说,IndoWaveSentiment是一个宝贵的资源.
- 该数据集有助于开发用于情绪分析的先进机器学习分类模型.
- 这项工作为情感计算和人机交互领域做出了贡献.
更多相关视频
05:51Exploring the Use of Isolated Expressions and Film Clips to Evaluate Emotion Recognition by People with Traumatic Brain Injury
Published on: May 15, 2016
9.0K
07:12Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation
Published on: August 26, 2016
9.4K
相关概念视频
Labeling Emotion
101
Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...
101
Classification of Signals
397
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
397
Aggregates Classification
303
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
303
Motional Emf
3.2K
Magnetic flux depends on three factors: the strength of the magnetic field, the area through which the field lines pass, and the field's orientation with respect to the surface area. If any of these quantities vary, a corresponding variation in magnetic flux occurs. If the area through which the magnetic field lines are passing changes, then the magnetic flux also changes. This change in the area can be of two types: the flux through the rectangular loop increases as it moves into the...
3.2K
Emotional Expression
166
Emotional expression encompasses how individuals convey their emotions through verbal communication and non-verbal cues. These non-verbal actions include facial expressions, body language, and physical gestures, such as frowning or smiling. Among these, facial expressions play a crucial role in emotional expression and are understood universally, indicating a biological basis for how humans communicate emotions.
Universal Facial Expressions
Psychologist Paul Ekman identified seven basic...
Universal Facial Expressions
Psychologist Paul Ekman identified seven basic...
166
Sound Intensity
4.0K
The loudness of a sound source is related to how energetically the source is vibrating, consequently making the molecules of the propagation medium vibrate. To measure the loudness of a source, the physical quantity of interest is the intensity. This is defined as the energy emitted per unit of time per unit of area perpendicular to the sound wave's propagation direction. Since the total energy is greater if the source vibrates for a longer duration and over a larger area, dividing the...
4.0K
