Powering the next generation of green microphones

This need for a new generation of green microphones leads to embedding the capability for waking up the rest of the system as soon as a voice activity is detected, possibly once a keyword has been spotted, while enhancing the recording quality with high sensitivity in far field and near field environments.

The combination of a complete Analog-to-Digital Converter (ADC) with a voice processing DSP has reached its limits for lowering power consumption. Voice detection by a DSP in always-listening mode is proving to be unsatisfactory for IoT applications powered by small batteries or even on a smartphone. Green microphones fill the low-power gap by dividing by a ratio of at least five the power consumption in always-listening mode.

To increase battery life far beyond any current solution, and to improve the sound recording quality, such green microphones require a new generation of ultra-low power voice triggers and fast response ADC modulators. The DSP then be embedded in the same SoC as the sound signal buffer and perform the ADC decimation and filtering functions.

Dolphin Integration, the mainstream provider of delta-sigma converters for audio applications, unveils the first silicon IP, mMOD67.5-ROOSTER-VD.01, targeting green microphones which combines an ultra-low power voice activity detector (WhisperTrigger-a) with an ultra-low power ADC modulator.Thanks to its self-adaptive design, the WhisperTrigger-a performs highly accurate voice detection, with a negligible detection latency, thus permitting efficient key-word spotting or speech-to-text recognitions by the DSP, whatever the user environment.

Performances of the mMOD67.5-ROOSTER-VD.01:

• Ultra-low power consumption: 25μA in Voice Detection mode and 360μA in full performance record mode from 20Hz to 20kHz, at Fmclk = 1.536MHz.
• SNR: 67.5dB at -26dBFs in the [20-20k] bandwidth (A-weighted), at Fmclk= 1.536MHz.
• Fast wake-up time of the ADC modulator: lower than 1ms.

Efficient detection performances in far-field context (per the MIWOK-C r1.0 benchmark):

• 27ms of average detection latency.
• 97.7% of Voice Detected as a Voice (VDV) within the first phoneme.
• 3.6% of Noise Detected as a Voice (NDV).