One concern with generative models is their computational complexity. Lyra avoids this issue by using a cheaper recurrent generative model, a WaveRNN variation, that works at a lower rate, but generates in parallel multiple signals in different frequency ranges that it later combines into a single output signal at the desired sample rate. This trick enables Lyra to not only run on cloud servers, but also on-device on mid-range phones in real time (with a processing latency of 90ms, which is in line with other traditional speech codecs). This generative model is then trained on thousands of hours of speech data and optimized, similarly to WaveNet, to accurately recreate the input audio.