Voice Activity Detection (VAD) is a technique used to identify the presence of human voice in
an audio signal. It is implemented as an always-on component in most speech processing …

Biomedical applications often require classifiers that are both accurate and cheap to
implement. Today, deep neural networks achieve the state-of-the-art accuracy in most …

The use of speech-triggered wake-up interfaces has grown significantly in the last few years
for use in ubiquitous and mobile devices. Since these interfaces must always be active …

Edge audio devices can reduce data bandwidth requirements by pre-processing input
speech on the device before transmission to the cloud. As edge devices are required to …

This paper presents a channel stereo-audio sensing front end with parallel asynchronous
event output inspired by the biological cochlea. Each binaural channel performs feature …

This paper describes digital circuit architectures for automatic speech recognition (ASR) and
voice activity detection (VAD) with improved accuracy, programmability, and scalability. Our …

This article presents the first keyword spotting (KWS) IC that uses a ring-oscillator-based
time-domain processing technique for its analog feature extractor (FEx). Its extensive usage …

Voice-controlled interfaces on acoustic Internet-of-Things (IoT) sensor nodes and mobile
devices require integrated low-power always-on wake-up functions such as Voice Activity …

Classifiers that can be implemented on chip with minimal computational and memory
resources are essential for edge computing in emerging applications such as medical and …

Ultralow-power sensing with inference functionality embedded in sensor nodes is essential
for enabling the emerging pervasive intelligence. For acoustic inference sensing, the feature …