Emotion Recognition Services for Machine Learning

You have an innate ability to understand non-verbal cues such as facial expressions, but do machines? With diverse image datasets labeled accurately, the answer is “Yes.”

Emotion Recognition

What is Emotion Recognition?

Emotion recognition put simply is a machine learning model’s ability to detect emotion in an image. This is first done through facial detection and recognition. Large amounts including different facial expressions are then collected and turned into your actionable dataset. Your Computer Vision model is trained with this dataset and is able to automatically identify and understand human emotion based on facial expression.

Why MarsCrowd?

A Crowd of

Trained Specialists

A Crowd of


A Crowd of

In-House Linguists

Emotion Recognition in Action

When we work together on a project, you can expect a seamless process for delivery. Emotion recognition can be broken down into 5 general steps from the raw upload of data to our in-house platform to the final delivery back to the end client. The overall goal is to correctly identify human emotion in image-based data. The process looks something like the model below:


Training of

classification model

Text Data Collection for Machine Learning Process

Text data collection

Design of

feature extractors

Performance evaluation & visualization

How Does Emotion Recognition Work?

Recorded audio can take various computer-readable formats such as wav, mp3, and WMA. These formats allow our Crowd to characterize audio based on parameters such as bandwidth, frequency, and decibels. Before using audio data to improve a machine learning model’s efficiency, audio data must be first categorized into classes of similar frequency and waves. These frequency-based features can then be extracted as input variables into a machine learning model to generate new audio such as a song or help machines understand a language’s unique characteristics.
The underlying problem for many models is a lack of high quality audio data. In order to get the most out of your model, make sure the data you’re feeding it is sufficient. Our global Crowd is able to not only help in the labeling of audio data, but can help you collect the data as well. Get your project off to the best possible start with MarsCrowd.

Get customized human-labeled now