Emotion Classification Dataset. - GitHub - Aarushi253/Emotion_Classification_ML: Developed M

- GitHub - Aarushi253/Emotion_Classification_ML: Developed ML models (Logistic Regression, SVM) to classify text-based emotions, achieving 80%+ accuracy The datasets represent a diverse collection of text types. Jan 7, 2026 · emotion, a complex experience of consciousness, bodily sensation, and behaviour that reflects the personal significance of a thing, an event, or a state of affairs. The classifier is trained using 2 different datasets, RAVDESS and TESS, and has an overall F1 score of 80% on 8 classes (neutral, calm, happy, sad, angry, fearful, disgust and The dataset is sourced from Kaggle. MindReader is an emotion detection project leveraging the Empathetic Dialogues dataset. It preprocesses data with Sentence-BERT embeddings and trains four deep learning models (CNN-GRU, CNN-BiGRU, CNN-LSTM, CNN-BiLSTM) for emotion classification. As MELD (Multimodal EmotionLines Dataset) extends the popular EmotionLines dataset, EmotionLines itself is not included here. This study re-categorizes ISEAR’s seven original emotions (joy, fear, anger, sadness, disgust, shame, guilt) into five groups (joy, fear, sadness, anger/disgust, neutral/shame/guilt) to align with Download scientific diagram | Deep Learning classifiers applied on Dog-emotion dataset from publication: Deep Learning Framework Facilitated Design, Development, and Analysis of Chronic Diarrhea Indonesian twitter dataset for emotion classification task - Forks · meisaputri21/Indonesian-Twitter-Emotion-Dataset 3 days ago · Computer vision dataset by @danny-wong on Ultralytics Platform. Emotions play a central and crucial role, integrating physiology, cognition, behavior, The Emotion Compass is a free site for everyone who wants to learn about emotions, explore their emotional style or work on their own emotions. emotion-classifcation-eeg Using Deep Learning for Emotion Classification on EEG signals (SEED Dataset). After preprocessing the data, features were extracted using Rhythm Abstract In this article we present the Amharic Speech Emotion Dataset (ASED), which covers four dialects (Gojjam, Wollo, Shewa, and Gonder) and five different emotions (neutral, fearful, happy, sad, and angry). This research presents an interdisciplinary framework that integrates mathematical optimization techniques with the deep neural networks to optimize learning rate for the ResNet architectures to be better for FER on the benchmark dataset FER2013+ for emotion classification. The dataset is sourced from Kaggle and consists of text data labeled with these six emotion categories. Emotion classification is critical for mental health chatbots, but label ambiguity in datasets like ISEAR (International Survey on Emotion Antecedents and Reactions) hinders model performance. About Trained a classifier to automatically detect emotions in short English texts, using a labelled dataset of English Twitter messages, where each tweet is labelled with one of six basic emotions : Anger (0), Fear (1), Joy (2), Love (3), Sadness (4), and Surprise (5). ” Emotions are how individuals deal with matters or situations they find personally significant. Nov 7, 2025 · Learn how to build an emotion classification model using Python and Keras CNN. A similar multi-componential description of emotion is found in sociology. Jun 27, 2019 · According to the American Psychological Association (APA), emotion is defined as “a complex reaction pattern, involving experiential, behavioral and physiological elements. Each expression is produced at two levels of emotional intensity (normal, strong), with an additional neutral expression. We believe it is the first Speech Emotion Recognition (SER) dataset for the Amharic language. Contribute to kabbi159/EmoInt-Emotion-Classification development by creating an account on GitHub. Oct 28, 2021 · While these emotion datasets enabled initial explorations into emotion classification, they also highlighted the need for a large-scale dataset over a more extensive set of emotions that could facilitate a broader scope of future potential applications. We introduce GoEmotions, the largest manually annotated dataset of 58k English Reddit comments, labeled for Project Overview This project aims to classify text into emotions such as sadness, joy, love, anger, fear, and surprise using machine learning techniques. Understanding emotion expressed in language has a wide range of applications, from building empathetic chatbots to detecting harmful online behavior. Learn about Emotion, APA's peer reviewed journal publishing significant contributions to the study of emotion from various theoretical traditions and research domains. Specifically, they contain emotion labels for texts from Twitter, Reddit, student self-reports, and utterances from TV dialogues. Explore and run machine learning code with Kaggle Notebooks | Using data from Face Emotion Image Dataset May 15, 2023 · Article on Robust Human Face Emotion Classification Using Triplet-Loss-Based Deep CNN Features and SVM, published in Sensors 23 on 2023-05-15 by Irfan Haider+3.

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