Google today open-sourced Lyra in beta, an audio codec that uses machine learning to produce high-quality voice calls. VentureBeat reports: The code and demo, which are available on GitHub, compress raw audio down to 3 kilobits per second for “quality that compares favorably to other codecs,” Google says. Lyra’s architecture is separated into two pieces, an encoder and decoder. When someone talks into their phone, the encoder captures distinctive attributes, called features, from their speech. Lyra extracts these features in 40-millisecond chunks and then compresses and sends them over the network. It’s the decoder’s job to convert the features back into an audio waveform that can be played out over the listener’s phone.
According to Google, Lyra’s architecture is similar to traditional audio codecs, which form the backbone of internet communication. But while these traditional codecs are based on digital signal processing techniques, the key advantage for Lyra comes from the ability of its decoder to reconstruct a high-quality signal. Google believes there are a number of applications Lyra might be uniquely suited to, from archiving large amounts of speech and saving battery to alleviating network congestion in emergency situations.