Google duo is testing a new codec to improve its call quality on poor network connections. The name of the new audio codec is Lyra. The company is training the new codec with open source audio libraries.
Various network providers are moving on to 5G networks. However, there are people who are still complaining about poor network connections in their area. Google duo is a video-conferencing application that allows users to communicate with other people using the VoIP interface.
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The issue
Google duo is famous for the transmission of high-quality audio during a video call. The audio codec of the application is best. However, this Codec is only successful at high-speed internet connections. If the network of the user is unstable or low then the user can barely understand the message.
When the internet connection is poor; the audio codec fails and the voice breaks during a call. This creates a big communication barrier between the users. That is why Google is improving its audio codec.
Lyra by Google duo
The new audio codec, Lyra is a low bit rate speech codec. Google Duo explains that the new codec extracts distinctive speech attributes in the form of log Mel spectrograms.
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Although, this is the architecture of traditional parametric codecs. The difference here is that Lyra will use a new high-quality audio generative model. With the help of this model, it can extract critical parameters from a speech and reconstruct it without using much data.
Google duo claims that Lyra does not send sample by sample over a signal. This process needs much more data. Whereas it uses a cheaper recurrent generative model. This model allows the new Codec to generate multiple signals at different frequencies. The codec then combines all the single output signals at the desired sample rate.
These new improvements will help Google duo to get better audio quality even on poor connections. Not only this but Google claims that Lyra will give a tough competition to codecs like Speex, MELP, and AMR.
The developers are training the audio codec with thousands of hours of audio. They are training the Codec with over 70 languages using an open-source audio library. They are testing the audio codec with exports and crowdsourced listeners.
