# Improving Minimal Gated Unit for Sequential Data

## TL;DR

This paper introduces an improved Minimal Gated Unit for sequential data processing by integrating Chrono Initializer, demonstrating enhanced speed and accuracy in tasks like machine translation and speech recognition.

## Contribution

The paper proposes using Chrono Initializer with the Minimal Gated Unit to improve its performance on sequential data tasks.

## Key findings

- Confirmed effectiveness of the proposed method
- Improved processing speed and accuracy
- Validated on adding and copy tasks

## Abstract

In order to obtain a model which can process sequential data related to machine translation and speech recognition faster and more accurately, we propose adopting Chrono Initializer as the initialization method of Minimal Gated Unit. We evaluated the method with two tasks: adding task and copy task. As a result of the experiment, the effectiveness of the proposed method was confirmed.