WN8033F is a SoC chip QFN40 that integrates domestic embedded CPU core CK804 (Flat Head Brother)

Product Descriptions

WN8033F is a high-performance, reliable, low-power, and low-cost SoC chip based on the domestic embedded CPU core CK804 (Flat Head Brother) with DSP enhancement and floating-point operation. It is equipped with 128K SRAM, 512KBFlash, SARADC, Timers/RTC/WDT, PWM, PMU and other peripheral devices, as well as USB, UART, SPI, I2C, I2S, GPIO and other I/O interfaces. It adopts SMIC 55nm LL technology and 40pin 4x4 QFN packaging, supporting multiple low-power modes. Mainly targeting digital voice and audio applications.

Product Features

• Built in 32-bit high-performance, low-power domestic embedded CPU core CK804 (Flat Head Brother), supporting single precision floating-point operation and DSP instruction acceleration. CPU unit performance of 1.5DMIPS/MHz, with a main frequency of up to 240MHz

• Built in 8KB BootROM, 128KB SRAM, 512KB Flash

• Rich peripheral interfaces: 32 bit Timers * 4 (supports Free running/user defined count), RTC, WDT, 12 channel 16 bit PWM, UART * 2, I2C, SPI, I2S * 2 (SPDIF multiplexing, supports 16 bit, 44.1/48KHz sampling rate), GPIO * 13, USB (control+PHY, supports 7in&7out endpoints), 7 external input channels 12-bit SARADC

• Architecture: Implement deep integration with digital audio processing and neural network computing from a chip architecture perspective

• Power consumption: DeepSleep (Standby) 10uA, Suspend 30uA, run @ 150M<45 mA

• Algorithm enhancement: Professional audio/sound effect processing algorithms to meet high-quality audio application requirements; A series of speech denoising and far-field speech algorithms are used to achieve high and reliable wake-up recognition rates, longer wake-up distances, lower false wake-up rates, stronger noise resistance, and faster response recognition times

  Product Applications

• Audio applications with high-quality audio requirements, such as wired (type-c/USB) and wireless esports earphones/earphones, karaoke earphones/earphones/audio systems, telephone/network conference speakers, etc

• Speech application scenarios that require background noise reduction, speech enhancement, and offline speech processing/recognition

  Specifications

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