An 8.62-μW 75-dB DRSoC Fully Integrated SoC for Spoken Language Understanding

We present a sub-10- $\mu $ W fully integrated SoC for on-device spoken language understanding (SLU). Its analog feature extractor (FEx) applies global and per-channel automatic gain control (AGC) to extend the system’s dynamic range (DR)—a critical requirement for real-world scenarios, including far-field operations. The on-chip streaming-mode recurrent neural network (RNN) accelerator exploits temporal sparsity and pooling, reducing its power by $2.3\times $ . By combining hardware-aware training with a behavioral model of the FEx that captures circuit nonidealities, the network is trained to maintain SLU accuracy despite chip-to-chip variation. Fabricated in a 65-nm CMOS process, the SoC occupies 2.23 mm² and consumes 8.62 $\mu $ W for end-to-end SLU. The 16-channel FEx achieves 93-dB DR while dissipating 1.85 $\mu $ W at 100-Hz feature frame rate. The SoC is evaluated on the 32-class Fluent Speech Commands dataset (FSCD), achieving 92.9% accuracy for 2.8-mV_rms inputs while maintaining >85% accuracy over a 75-dB input range.