Compressing Streaming Neural Audio Encoders via Latent-Space Distillation

Apple researchers have introduced a method called latent-space distillation to compress streaming neural audio encoders used in on-device speech transcription. By distilling complex models into more compact versions, this technique reduces the computational resources required for devices to map raw waveforms into representations that foundation models can process. This approach helps maintain high-quality dictation performance while decreasing the memory and latency demands of real-time speech recognition on mobile hardware.