Connect with random people instantly. Find them in the world’s largest group chat. The “Omegle” for people who don’t want to get creepy messages from old people and weird strangers! Free private chat forever, and meet people along the way. Zonish is also great for you to contact your friends anonymously. Zonish.com is also the best way to contact your friends anonymously, without your parents finding out! Our site is pretty much a way for you to launder your chats. Statistically, the chance of someone finding your chat is impossible, unless they are with you in real life, looking at your computer or device. We hope to make the internet a safer and more secure place for everyone to chat on, without the risks of being spied on, by anyone untrustworthy. Talking to strangers online can be sketchy, so if you are ever talking to someone you don’t feel comfortable with, please just leave the chat. If you are reading this, please let us know if you have any ideas, questions, or concerns for our website here: [email protected] Thanks for reading and enjoy chatting!

Debiasing Speech Recognition Systems for Kids


Image says, “Dibiasing.” In the background is a silhouette of a person’s head, and the image also includes some fun colourful shapes.

Welcome to Lesson 4 in our “Lessons from Our Voice Engine” series, featuring high-level insights from our Engineering and Speech Tech teams on how our voice engine works. This lesson is from Dr. Amelia Kelly, VP of Speech Technology.

What is debiasing?

Artificial intelligence systems will reflect the conscious and unconscious biases of their creators and create poor — and often prejudicial — user experiences for underrepresented users. Machine learning algorithms are unique in that they carry out decisions based on what they’ve seen within a supplied dataset, rather than being explicitly programmed using a predetermined set of rules. Building a system based largely on data from one demographic will result in accurate performance of the speech recognition system for that sub-group, but inaccurate performance for all others.

Debiasing is the conscious and intentional process of counteracting inherent biases that are found in databases and artificial intelligence systems.

Intentional processes, such as utilizing a varied, diverse, and proportionately representative dataset of voices to train machine learning algorithms, can reduce or remove the presence of unintended bias in voice technologies.

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Why is debiasing important for our voice engine and AI systems in general?

A biased system can amplify and propagate deep-seated prejudices held by the designers of that system, be they explicit or unintended. The effects of such biases in the context of educational technology, assessment platforms and learning tools for kids can be disastrous.

For example, if a biased system fails to understand a child’s accent or dialect, it can consistently tell that child he or she is a poor reader when, in fact, they are reading correctly. An unbiased system, on the other hand, can offer fair and uncompromised information to facilitate edtech platforms and services. AI companies need to make a concerted effort to debias their technology.

Catch up on our previous “Lessons from Our Voice Engine”:

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Debiasing Speech Recognition Systems for Kids was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.