Event-Driven Local Gain Control on a Spiking Cochlea Sensor

Kiselev, Ilya; Liu, Shih-Chii

doi:10.1109/iscas51556.2021.9401742

Cited by 4 publications

(3 citation statements)

References 28 publications

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“…In addition, it is difficult to separate individual sound sources from a mixed acoustic signal and to generalize to unknown acoustic conditions. Automatic adaptation that can overcome some of these issues is currently being implemented at the signal processing level (that is, nonlinear filtering) or at the network stage [21][22][23] . Although basic tasks like voice activity detection, keyword spotting and speech detection with a limited vocabulary have been implemented on low-power devices 24,25 , this has yet to be achieved for more complex applications such as acoustic scene analysis.…”

Section: Sensing Propertiesmentioning

confidence: 99%

“…Since all the three parameters can be individually controlled, short-term and long-term adaptations targeting amplitude and frequency ranges can be easily implemented. This enables the combination of, for instance, a fast adaptation of the sensor to the onset of sound signals (similar to sensory adaptation 3 ) or automatic gain control to avoid damage due to high SPLs with slow adaptation, similar to homoeostatic control keeping the sensing amplitude in a pre-defined range 11,22 . Such adaptations can be used to increase the dynamic range, implement event-based sensing and spike-rate-based encoding of sound properties, as well as cover large frequency ranges with only a few transducers and still retaining high-frequency resolution.…”

Section: Dynamical Adaptationmentioning

confidence: 99%

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Neuromorphic acoustic sensing using an adaptive microelectromechanical cochlea with integrated feedback

et al. 2023

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Many speech processing systems struggle in conditions with low signal-to-noise ratios and in changing acoustic environments. Adaptation at the transduction level with integrated signal processing could help to address this; in human hearing, transduction and signal processing are integrated and can be adaptively tuned for noisy conditions. Here we report a microelectromechanical cochlea as a bio-inspired acoustic sensor with integrated signal processing functionality. Real-time feedback is used to tune the sensing and processing properties, and dynamic switching between linear and nonlinear characteristics improves the detection of signals in noisy conditions, increases the sensor dynamic range and enables adaptation to changing acoustic environments. The transition to nonlinear behaviour is attributed to a Hopf bifurcation and we experimentally validate its dependence on sensor and feedback parameters. We also show that output-signal coupling between two coupled sensors can increase the frequency coverage.

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Section: Sensing Propertiesmentioning

confidence: 99%

Section: Dynamical Adaptationmentioning

confidence: 99%

Neuromorphic acoustic sensing using an adaptive microelectromechanical cochlea with integrated feedback

et al. 2023

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“…Because of the challenges in designing on-chip local gain control circuits, we recently proposed a system-level channelspecific AGC mechanism that uses the spiking activity of the individual filter channels on a DAS spiking cochlea to dynamically adapt the local gain of the filters [31]. This realtime AGC mechanism does not use floating-point arithmetic; instead, it only needs counters and comparators that can be implemented at low hardware cost on a future cochlea ASIC.…”

Section: Introductionmentioning

confidence: 99%

Spiking Cochlea With System-Level Local Automatic Gain Control

Kiselev

Gao

Liu

2022

IEEE Trans. Circuits Syst. I

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Including local automatic gain control (AGC) circuitry into a silicon cochlea design has been challenging because of transistor mismatch and model complexity. To address this, we present an alternative system-level algorithm that implements channel-specific AGC in a silicon spiking cochlea by measuring the output spike activity of individual channels. The bandpass filter gain of a channel is adapted dynamically to the input amplitude so that the average output spike rate stays within a defined range. Because this AGC mechanism only needs counting and adding operations, it can be implemented at low hardware cost in a future design. We evaluate the impact of the local AGC algorithm on a classification task where the input signal varies over 32 dB input range. Two classifier types receiving cochlea spike features were tested on a speech versus noise classification task. The logistic regression classifier achieves an average of 6% improvement and 40.8% relative improvement in accuracy when the AGC is enabled. The deep neural network classifier shows a similar improvement for the AGC case and achieves a higher mean accuracy of 96% compared to the best accuracy of 91% from the logistic regression classifier.

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Bio-inspired, Neuromorphic Acoustic Sensing

Lenk,

Ved,

Durstewitz

et al. 2023

Springer Series on Bio- And Neurosystems

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We present an overview of recent developments in the area of acoustic sensing that is inspired by biology and realized by micro-electromechanical systems (MEMS). To support understanding, an overview of the principles of human hearing is presented first. After the review of bio-inspired sensing systems, we continue with an outline of an adaptable acoustic MEMS-based sensor that offers adaptable sensing properties due to a simple, real-time feedback. The transducer itself is based on an active cantilever, which offers the advantage of an integrated deflection sensing based on piezoresistive elements and an integrated actuation using thermomechanical effects. We use a feedback loop, which is realized via a field-programmable gate array or analog circuits, to tune the dynamics of the sensor system. Thereby, the transfer characteristics can be switched between active, linear mode, for which the sensitivity and minimal detectable sound pressure level can be set by the feedback strength (similar to control of the quality factor), and an active nonlinear mode with compressive characteristics. The presented sensing system, which is discussed both from an experimental and theoretical point of view, offers real-time control for adaptation to different environments and application-specific sound detection with either linear or nonlinear characteristics.

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Event-Driven Local Gain Control on a Spiking Cochlea Sensor

Cited by 4 publications

References 28 publications

Neuromorphic acoustic sensing using an adaptive microelectromechanical cochlea with integrated feedback

Neuromorphic acoustic sensing using an adaptive microelectromechanical cochlea with integrated feedback

Spiking Cochlea With System-Level Local Automatic Gain Control

Bio-inspired, Neuromorphic Acoustic Sensing

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