SuperChat: Dialogue Generation by Transfer Learning from Vision to Language using Two-dimensional Word Embedding and Pretrained ImageNet CNN Models

05/07/2019
by   Baohua Sun, et al.
0

The recent work of Super Characters method using two-dimensional word embedding achieved state-of-the-art results in text classification tasks, showcasing the promise of this new approach. This paper borrows the idea of Super Characters method and two-dimensional embedding, and proposes a method of generating conversational response for open domain dialogues. The experimental results on a public dataset shows that the proposed SuperChat method generates high quality responses. An interactive demo is ready to show at the workshop.

READ FULL TEXT
research
05/25/2019

SuperCaptioning: Image Captioning Using Two-dimensional Word Embedding

Language and vision are processed as two different modal in current work...
research
10/26/2021

Task-Specific Dependency-based Word Embedding Methods

Two task-specific dependency-based word embedding methods are proposed f...
research
01/24/2019

Squared English Word: A Method of Generating Glyph to Use Super Characters for Sentiment Analysis

The Super Characters method addresses sentiment analysis problems by fir...
research
06/04/2019

System Demo for Transfer Learning across Vision and Text using Domain Specific CNN Accelerator for On-Device NLP Applications

Power-efficient CNN Domain Specific Accelerator (CNN-DSA) chips are curr...
research
10/15/2018

Super Characters: A Conversion from Sentiment Classification to Image Classification

We propose a method named Super Characters for sentiment classification....
research
04/28/2020

Conversational Word Embedding for Retrieval-Based Dialog System

Human conversations contain many types of information, e.g., knowledge, ...
research
01/31/2021

Introduction of a novel word embedding approach based on technology labels extracted from patent data

Diversity in patent language is growing and makes finding synonyms for c...

Please sign up or login with your details

Forgot password? Click here to reset