Features
AWINIC Audio Neural Processing Unit(A-NPU^TM): A-NPU^TM supports neural networks such as DNN, TDNN, RNN, and CNN, as well as parallel vector operations. It can realize functions including deep learning noise reduction, sound source localization, and echo cancellation
CPU and memory: The CPU clock speed can reach 240 MHz; Built-in 4MBytes Flash memory; Built-in 640KBytes SRAM; Built-in 512-bit eFuse, can be used for application encryption;
Audio Codec: High-performance, low-power audio ADC, SNR ≥ 95dB; Low-power audio DAC, SNR ≥ 95dB;
Audio Interface: 1-way IIS interface, supports configurable master-slave; 1-channel dual-path PDM interface;
ADC and PWM: Built-in 4-channel 12-bit SAR ADC; Supports 6 PWM interfaces;
GPIO: 26 high-speed GPIOs with a response rate of up to 20MHz; Among them, 18 GPIOs support 5V input;
Reset and power management: Built-in Power Management Unit (PMU); PMU input voltage range: 3.6V to 5.5V; Built-in Power-On Reset (POR); Built-in Voltage Detection (PVD);
Clock: Built-in RC oscillator, also supports external crystal oscillator; developers can choose to use either the built-in RC or an external crystal as the chip clock source depending on different application scenarios;
Communication interface: 1-channel IIC interface; 3 UART interfaces, supporting 5V and up to 3Mbps speed;
Timers and Watchdogs: Built-in 4 sets of 32-bit timers and 2 sets of watchdogs;
Description
AWA89601 is Awinic's high-performance intelligent voice chip, integrating the A-NPU^TM and CPU core, with a main frequency of 240MHz. It features 640KB of built-in SRAM and rich peripherals such as PMU and audio codecs, requiring only minimal external components to build a high-cost-performance intelligent voice solution.
The chip meets industrial-grade standards, with an operating temperature range of -40°C to 85°C, and complies with multiple reliability certifications such as MSL3, 2KV contact discharge, FCC EMC, ROHS, and REACH.
A-NPU^TM technology supports mainstream neural networks such as DNN, RNN, and CNN, features deep learning noise reduction, sound source localization, and echo cancellation.
