Official Code for SIGIR 2022 "A Multi-task Based Neural Model to Simulate Users in Goal Oriented Dialogue Systems". User Simulator generates user-side utterance, predicts user's next action and satisfaction level.

"Simulating User Satisfaction for the Evaluation of Task-oriented Dialogue Systems" in SIGIR'21

A complete machine-learning system that predicts AI assistant user satisfaction using behavioral signals such as device, usage category, time features, session metrics, and model metadata. Includes full ML pipeline, SHAP explainability, evaluation suite, and an interactive Streamlit analytics dashboard.

Manage your apdex

Aspect Based ReDial(AB-ReDial): Is a subset data from ReDial annotated on six dialogue aspects and overall user satisfaction at the turn and dialogue levels with the following aspects; relevance, interestingness, understanding, task completion, interest arousal, and efficiency

Metric-Apdex is an extension to Dropwizards's metrics library which enhances the existing Gauge metric type and provide it with the capability to calculate Apdex score by converting the measurements into insights about user satisfaction.

This project analyzes customer satisfaction and user sentiment based on 215,000+ user reviews of the Gojek mobile application written in Bahasa Indonesia.

A Rust crate for calculating Net Promoter Score (NPS) from survey responses.

This repo contains outcomes across all stages of the thematic analysis conducted on the reasons to be satisfied or dissatisfied when using the virtual coach.

Este trabajo presenta una herramienta web para automatizar la medición de la satisfacción del usuario en pruebas de usabilidad, mediante análisis de sentimientos en respuestas abiertas. La solución integra una API en Python y un cliente web en React, conectados para asegurar evaluaciones eficientes y objetivas.