Expanding background noise suppression across platforms and scenarios

Published Jun 07 2022 08:00 AM 8,523 Views

Over 270 million active users rely on Microsoft Teams to connect, share, learn, and collaborate, which affirms our commitment to continually improving call quality. In a previous Teams Blog post, we introduced machine-learning-based noise suppression, which automatically removes unwanted background sounds from calls and meetings. Since then, we have been working to expand the reach of this feature to more platforms and scenarios. After its initial release on Windows, background noise suppression is now available on Mac and iOS as well.

 

After the release of Teams background noise suppression for Windows users as an optional feature, we went through an iterative development and evaluation cycle to optimize our model and advance broader research in this field. With this goal in mind, we launched various competitions including our latest at the International Conference on Acoustics, Speech and Signal Processing 2022, and open-sourced both our dataset and the perceptual quality crowdsourcing framework.


These events helped improve the quality and complexity of our model. Our iterative experimentation process showed that improved call quality led to an increase in call duration for one-on-one calls. We also saw a 32% reduction in complaints of background noise reported in our end-of-call survey. Considering the significance of these improvements, we enabled machine-learning-based noise suppression as default for Teams customers using Windows. The same experiments were also conducted for Mac and iOS which showed similar improvements, leading us to release this feature as default on these platforms as well. This change of enabling noise suppression by default for most calls makes this feature the most widely used AI feature in Microsoft Teams, but more importantly improving experiences for millions of users who confidently take Teams calls and meetings from anywhere.


In addition to this extended platform coverage, we have also been working to make machine-learning-based noise suppression available on an expanded range of device types, including support for ARM-based devices and Microsoft Teams Rooms.


While the user benefits from machine-learning-based noise suppression appear obvious and ubiquitous, we were mindful of scenarios where it’s important to not suppress non-speech content, such as during music lessons. While it may be desirable that your kid’s music practice doesn’t disturb your work meeting, we also want to avoid negatively impacting the teacher’s ability to conduct the music lesson over Teams.


To differentiate those use-cases, we have implemented music detection into the noise suppression capability. This feature alerts users when AI identifies music so they can choose to disable noise suppression and enable transmitting music via our “High-fidelity Music Mode”. Music detection has been released for our desktop Windows client and has allowed us to turn on machine-learning-based noise suppression by default for our education customers as well. A future release of this feature is planned for education users on Mac and iOS devices as well as across all Teams Android and web clients.


While we’re excited about the advancements in Teams call quality we’ve achieved through machine-learning and AI, we’re just beginning to realize the opportunities ahead. Keep watching this blog to learn how innovation, testing, and optimization enables us to continually improve meeting and call quality in Teams.

 

 

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