Methods for Emotion Classification in Text

Applicant

Google

Auteurs

N/A

Titre

Methods for Emotion Classification in Text

Patent Number

US2022292261

Publication Date

2022

uri

https://patents.google.com/patent/US20220292261

Description

The technology relates to methods for detecting and classifying emotions in textual communication and using this information to suggest graphical indicia such as emoji, stickers or GIFs to a user. Two main types of models are fully supervised models and few-shot models. In addition to fully supervised and few-shot models, other types of models focusing on the back-end (server) side or client (on-device) side may also be employed. Server-side models are larger-scale models that can enable higher degrees of accuracy, such as for use cases where models can be hosted on cloud servers where computational and storage resources are relatively abundant. On-device models are smaller-scale models, which enable use on resource-constrained devices such as mobile phones, smart watches or other wearables (e.g., head mounted displays), in-home devices, embedded devices, etc.

keywords

Emotion

Domaine de recherche

Computer-Mediated Communication

Natural Language Processing

Sentiment Analysis

Social Media and User Engagement

Données collectées (type source)

Text

Concepts clés

Emotion

Méthode

Supervised models and few-shot models. Using machine-learned models to detect/classify direct versus induced emotion, notably based on text and emoticons

Dispositif

Device

Objectifs du brevet

Determine/Identify User Emotion

Personalize/Improve with emotion information

Promote the expression of user's emotion