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Aspinity Detects Voice in Analog Nets

July 2, 2019

Author: Mike Demler

Aspinity’s Reconfigurable Analog Modular Processor (Ramp) provides always-on capability in low-power voice-activated devices, drawing just 10 microamps during active operation. Ramp is a voice-activity detector (VAD); it integrates a small analog neural network that consumes just 10% as much power as its nearest digital competitor.

Sound waves are analog, so some digital VADs integrate an analog-to-digital converter (ADC) that transforms microphone outputs. A more popular solution is a smart microphone that outputs pulse-density-modulated (PDM) digital signals, but such devices just move the ADC into the sensor. Either way, the ADC is a power drain in battery-operated devices because it continuously consumes at least 100 microwatts. Ramp doesn’t eliminate the ADC, but it saves power by keeping this component and the rest of the signal-processing chain in sleep mode until a speech signal arrives.

The chip’s low power is due to its subthreshold circuits. MOS transistors operating in subthreshold mode normally suffer leakage current, but for low-power analog circuits, that mode also yields an exponential transconductance that’s useful in amplifiers and similar circuits. Subthreshold circuits are slow because of their high output impedance, but they draw little supply current as a result.

Ramp is well suited to smart headphones, smartwatches, and other devices that use an ADC and DSP intermittently. In addition to producing the discrete chip, Aspinity plans to offer its intellectual property for more-highly integrated voice processors, benefitting voice assistants. The analog detector keeps them from streaming when they’re not being spoken to, and it turns them off more quickly than a roundtrip to the cloud would allow, maintaining privacy much better than the always listening Alexa and Siri.

Subscribers can view the full article in the Microprocessor Report.

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