ANITA: ANImal TrAnslator

In recent years there has been an explosive growth in neural network based algorithms for interpretation and generation of natural language.

One task that has been addressed successfully using neural approaches is machine translation from one language to another.The goal of the project proposed here is to make an automated interpreter of animal communicative behavior to human language, in order to allow humans to get an insight into the mind of animals in their care.

We focus on three species: dog, horse and cattle. There are two reasons for focusing on several species.

Firstly, there are many common denominators in their behavior and interaction, which means that we can gain generic knowledge about their behavior from cross-species studies.

Secondly, each species have their distinct challenges and distinct potential impacts.Despite the high potential impact, automated animal behavior recognition is still an undeveloped field.

The reason is not the signal itself; these domestic species have developed for thousands of years together with humans, and have rich communication and interaction both with humans and with other animal individuals.

The main difference from the human language field is instead the lack of data; large data volume is a key success factor in training large neural language models.

Thus, data collection is an important venture in this project.Using this data, we propose to develop a deep generative approach to animal behavior recognition from video.