#Emotion
Showing 31 of 31 repositories tagged #emotion, ranked by stars
👩🎤 CSS-in-JS library designed for high performance style composition
EmotiVoice 😊: a Multi-Voice and Prompt-Controlled TTS Engine
🦹♂️ Twin blends the magic of Tailwind with the flexibility of css-in-js (emotion, styled-components, solid-styled-components, stitches and goober) at build time.
:atom_symbol: React primitive UI components built with styled-system.
⬢ Style props for rapid UI development
Build consistent, themeable React apps based on constraint-based design principles
🥜 goober, a less than 1KB 🎉 css-in-js alternative with a familiar API
A utility-first CSS-in-JS framework built for React. 💅👩🎤⚡️
This package has moved and renamed
Universal React+GraphQL starter kit: React 16, Apollo 2, MobX, Emotion, Webpack 4, GraphQL Code Generator, React Router 4, PostCSS, SSR
The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)
React UI components of the Yamada, by the Yamada, for the Yamada built with React and Emotion.
A deep neural net toolkit for emotion analysis via Facial Expression Recognition (FER)
Winner of Mozilla's $50,000 prize for AI
Useful interpolated functions for CSS-in-JS
Powerful CSS-in-JS media queries with SSR support.
👩🎨 Access your design tokens with ease
Understanding emotions from audio files using neural networks and multiple datasets.
:rocket: A basis for reducing the configuration of your projects with nextJS, best development practices and popular libraries in the developer community.
🌑 Enable dark mode for Next.js apps
Develop themable components with Emotion/Styled Components/Material-UI with help of Storybook & React Theming
[OUTDATED] React 16.8.4 + NextJS 8.0.3 + Emotion + Sequelize 5/Postgres + Passport Local Auth + Google App Engine or Heroku Deployment
Explore transactions and accounts on the Stacks blockchain. Clone any contract and experiment in your browser with the Explorer sandbox.
Voice stress analysis (VSA) aims to differentiate between stressed and non-stressed outputs in response to stimuli (e.g., questions posed), with high stress seen as an indication of deception. In this work, we propose a deep learning-based psychological stress detection model using speech signals. With increasing demands for communication between humans and intelligent systems, automatic stress detection is becoming an interesting research topic. Stress can be reliably detected by measuring the level of specific hormones (e.g., cortisol), but this is not a convenient method for the detection of stress in human- machine interactions. The proposed algorithm first extracts Mel- filter bank coefficients using pre-processed speech data and then predicts the status of stress output using a binary decision criterion (i.e., stressed or unstressed) using CNN (Convolutional Neural Network) and dense fully connected layer networks.
Emotion recognition by speech in android.
An in-depth analysis of audio classification on the RAVDESS dataset. Feature engineering, hyperparameter optimization, model evaluation, and cross-validation with a variety of ML techniques and MLP
🎹 Moodify - an emotion-based music recommendation system that uses AI/ML models to analyze text, speech, and facial expressions, providing personalized music recommendations across web and mobile platforms.
The main purpose of the project - recognition of emotions based on facial expressions. Cohn-Kanade data set (http://www.pitt.edu/~emotion/ck-spread.htm) is used for explorations and training
Group Emotion Recognition using deep neural networks and Bayesian classifiers.
Scripts for exploring emotions in GitHub messages
Long-term analysis of emotion, age, and sentiment using Lifeslice and text records.