A 0.5 V 55 mu W 64 x 2 Channel Binaural Silicon Cochlea for Event-Driven Stereo-Audio Sensing

作者：Yang Minhao^*; Chien Chen Han; Delbruck Tobi; Liu Shih Chii

来源：IEEE Journal of Solid-State Circuits, 2016, 51(11): 2554-2569.

DOI：10.1109/JSSC.2016.2604285

• Adaptive adaptive self-oscillating comparison comparison
• asynchronous delta modulator (ADM)
• audio sensing
• bandpass filter (BPF)
• central frequency
• event-driven
• quality factor
• reconstruction
• silicon cochlea
• source follower
• speech
• spike
• vowel discrimination

This paper presents a 64 x 2 channel stereo-audio sensing front end with parallel asynchronous event output inspired by the biological cochlea. Each binaural channel performs feature extraction by analog bandpass filtering, and the filtered signal is encoded into events via asynchronous delta modulation (ADM). The channel central frequencies f(0) are geometrically scaled across the human hearing range. Two design techniques are highlighted to achieve the high system power efficiency: source-follower-based bandpass filters (BPFs) and asynchronous delta modulation (ADM) with adaptive self-oscillating comparison. The chip was fabricated in 0.18 mu m 1P6M CMOS, and occupies an area of 10.5x4.8 mm(2). The core cochlea system operating under a 0.5 V power supply consumes 55 mu W at an output rate of 100k event/s. The measured range of f(0) is from 8 Hz to 20 kHz, and the BPF quality factor Q can be tuned from 1 to almost 40. The 1 sigma mismatch of f(0) and Q between two ears is 3.3% and 15%, respectively, across all channels at Q approximate to 10. Reconstruction of speech input from the event output of the chip is performed to validate the information integrity in event-domain representation, and vowel discrimination is demonstrated as a simple application using histograms of the output events. This type of silicon cochlea front end targets integration with embedded event-driven processors for low-power smart audio sensing with classification capabilities, such as voice activity detection and speaker identification.

• 出版日期2016-11