AI can now listen to individuals in a crowd
This new breakthrough will let our Connected Home devices hear us better, but on the other it also gives organisations the ability to eavesdrop on everyone.
Key takeaways
- Devices like Amazon’s Echo and Google Home can normally deal with requests from a single person, but like us they often still struggle when there are lots of people talking at once, like, say at a party.
- Meinke says the system can separate and reconstruct the speech of five people speaking into a single microphone with up to 90 per cent accuracy, and if there are ten speakers the accuracy dips, but is still up to 80 per cent.
- Conventional approaches to this problem, such as using two microphones to replicate the position of a listener’s ears, have only managed 51 per cent accuracy.
Cite or link to this article
Griffin, M. (2017) 'AI can now listen to individuals in a crowd', 311 Institute, 20 November. Available at: https://www.311institute.com/ai-can-now-listen-to-individuals-in-a-crowd/ (Accessed: 1 October 2026).
Devices like Amazon’s Echo and Google Home can normally deal with requests from a single person, but like us they often still struggle when there are lots of people talking at once, like, say at a party.
Now though that might be less of a problem thanks to a new Artificial Intelligence (AI) agent that can separate the voices of multiple speakers out in real time, and it promises to give automatic speech recognition a big boost, and if it was ever combined with something like Google DeepMind's AI lip reading technology, that was recently proven to be much more accurate than the best human lip readers, then you'll never have to worry about being heard by AI ever again. And I'm almost certain that noone will ever think of using this technology to eavesdrop on you all...
The technology, which was developed by researchers at the Mitsubishi Electric Research Laboratory in Cambridge, Massachusetts, was demonstrated in public for the first time at this month’s Combined Exhibition of Advanced Technologies show in Tokyo.
It uses a machine learning technique the team calls “Deep Clustering” to identify unique features in the voiceprint of multiple speakers, and then it groups the distinct features from each speaker’s voice together, letting it disentangle multiple voices and then letting it reconstruct what each person was saying.
“It was trained using one hundred English speakers, but it can separate voices even if a speaker is Japanese,” says Niels Meinke, a spokesperson for Mitsubishi Electric.
Meinke says the system can separate and reconstruct the speech of five people speaking into a single microphone with up to 90 per cent accuracy, and if there are ten speakers the accuracy dips, but is still up to 80 per cent. In both cases though, this was with speakers the system had never encountered before.
Conventional approaches to this problem, such as using two microphones to replicate the position of a listener’s ears, have only managed 51 per cent accuracy.
In overcoming the “cocktail party effect” that has dogged AI research for decades, the new technology could help smart assistants in homes and cars work better, it could also improve automatic speech transcription, and, naturally, be used to help law enforcement agencies reconstruct recordings of conversations that could otherwise be incomprehensible.
In preliminary tests the system was able to successfully separate the voices of up to five people at once.
“The system could be used to separate speech in a range of products including lifts, air-conditioning units and household products,” says Meinke, and now he and his team are looking to integrate the technology into a number of products that they expect to be released into the market soon.
Their work was published in arxiv.org/abs/1508.04306
FAQ
Why does this matter?
This new breakthrough will let our Connected Home devices hear us better, but on the other it also gives organisations the ability to eavesdrop on everyone.

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
- 51 per cent accuracy researchgate.net
- arxiv.org/abs/1508.04306 arxiv.org
Source: first published by the 311 Institute on 20 November 2017. Cite as: Griffin, M. (2017). AI can now listen to individuals in a crowd. 311 Institute. https://www.311institute.com/ai-can-now-listen-to-individuals-in-a-crowd/
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