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Doctor Dolittle researchers use AI to decode mice chatter

Using AI to translate human languages is nothing new, but now we're using the technology to help us decipher animal languages.

Key takeaways

  • Dubbed DeepSqueak, the software program can analyse rodent vocalisations and then pattern-match the audio to behaviors observed in laboratory settings.
  • Published this week in the journal Neuropsychopharmacology, the study is based around a novel use of sonogram technology, which transforms an audio signal into an image or series of graphs.
  • The technology represents the first use of deep learning in rodent vocalisation research, said study co-author Russell Marx in a statement.
Cite or link to this article

Griffin, M. (2019) 'Doctor Dolittle researchers use AI to decode mice chatter', 311 Institute, 2 May. Available at: https://www.311institute.com/doctor-dolittle-researchers-use-ai-to-decode-mice-chatter/ (Accessed: 1 October 2026).

Dolphins are getting in on the act, and now so are mice – having their language translated into something humans can understand using Artificial Intelligence (AI) in what seems to be an increasingly interesting field that’s using AI to help us create a new breed of universal translators that help us decode and translate not just other human languages, but also animal language. Doctor Doolittle has competition…

In what is somehow the cutest science story of the new year so far, apparently, scientists at the University of Washington (UW) have announced a new AI system for decoding mouse squeaks.

Dubbed DeepSqueak, the software program can analyse rodent vocalisations and then pattern-match the audio to behaviors observed in laboratory settings. As such, the software can be used to partially decode the language of mice and other rodents, and researchers hope that the technology will be helpful in developing a broad range of medical and psychological studies.

Published this week in the journal Neuropsychopharmacology, the study is based around a novel use of sonogram technology, which transforms an audio signal into an image or series of graphs.

The DeepSqueak program turns recordings of mouse chatter into visual output, which is then analysed using advanced machine learning algorithms. In fact, the algorithms are in the same family as those used by self-driving cars to “see” their environment. The technology represents the first use of deep learning in rodent vocalisation research, said study co-author Russell Marx in a statement.

One critical advantage to the DeepSqueak system is that it can “hear” vocalizations that are otherwise inaudible to human ears.

“As it turns out, rats and mice have this rich vocal communication, but it's way above our hearing range, so it's been really hard to detect and analyze these calls,” Russell says in a project demo video. “Our software allows us to visualize all those calls, look at their shape and structure and categorize them.

See the tech in action
 

Marx and DeepSqueak co-creator Kevin Coffey, who both study addiction and psychology issues at UW have already made some interesting discoveries. Their initial efforts have focused on discerning calls of happiness or distress when working with mice in addiction experiments.

“The animals have a rich repertoire of calls, around 20 kinds,” said Coffey. “With drugs of abuse, you see both positive and negative calls.”

The mice appear to be happiest when they are anticipating a reward such as sugar, Coffey noted, but they also make happy calls in certain social situations. The researchers also observed that male mice make the same calls over and over when they’ re around other males, but switch to more complex vocalisations when females are nearby.

There’ s probably an entire shelf full of future sociological research in that one observation, but for now the team’s goal is to use the new technology for advancing addiction research.

John Neumaier, professor of psychiatry and behavioural sciences and associate director of the Alcohol and Drug Abuse Institute, said that DeepSqueak should help his lab make better and faster progress in the field by making vocalisation analysis convenient, efficient, and affordable.

“If scientists can understand better how drugs change brain activity to cause pleasure or unpleasant feelings,” he said, “we could devise better treatments for addiction.”

Source: Nature

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Why does this matter?

Using AI to translate human languages is nothing new, but now we're using the technology to help us decipher animal languages.

Matthew Griffin

About the author

Matthew Griffin Founder, 311 Institute

Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath."

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Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath." 15-time best selling author of the "Codex of the Future" series, Matthew is the Founder and Futurist in Chief of the 311 Institute, a global Futures and Deep Futures advisory firm working with royal households, world leaders, G7, G20, and G77 governments, NGOs, and multi-national mid and mega cap firms to help them explore, shape, and lead the next 50 years of business and society.

An award-winning YouTube creator with over a million followers, with an unrivalled global reach and impact, Matthew is a highly sought-after international keynote speaker, lecturer, and mentor who collaborates with global leaders through the United Nations Alliance of Civilizations (UNAOC) and United Nations General Assembly (UNGA) to shape pivotal initiatives such as the UN’s AI for Humanity program, the United Nations Conference of the Parties (UN COP), and the World Economic Forum in Davos.

As the former Global Head of Cloud, National Security, and Enterprise Sales for companies including Atos, Dell-EMC, and IBM, Matthew has a proven track record of building multi-billion dollar business units and turning failing divisions into market leaders. His ability to identify, analyse, and communicate the implications of hundreds of emerging technologies and trends is unparalleled, and his insights are trusted by many of the world’s most respected organisations, including ABB, Accenture, Adidas, AON, ARM, BCG, Centrica, Citi, Coca-Cola, Dentons, Deloitte, Dow Jones, EY, Google, KPMG, Lego, Legal & General, LinkedIn, Microsoft, PepsiCo, Qualcomm, RWE, Samsung, Siemens AG and Siemens Energy, T-Mobile, UBS, VISA, Walmart, Workday, Worldpay and many others.

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Sources and further reading

  1. S41386 018 0303 6 nature.com

Source: first published by the 311 Institute on 2 May 2019. Cite as: Griffin, M. (2019). Doctor Dolittle researchers use AI to decode mice chatter. 311 Institute. https://www.311institute.com/doctor-dolittle-researchers-use-ai-to-decode-mice-chatter/

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