Our application requires a keyword spotting system with a small memory footprint, low
computational cost, and high precision. To meet these requirements, we propose a simple …

The goal of keyword spotting is to detect the presence of specific spoken words in
unconstrained speech. The majority of keyword spotting systems are based on generative …

We present a novel approach to query-by-example keyword spotting (KWS) using a long
short-term memory (LSTM) recurrent neural network-based feature extractor. In our …

We propose a sub-μW always-ON keyword spotting (μKWS) chip for audio wake-up
systems. It is mainly composed of a neural network (NN) and a feature extraction (FE) circuit …

Intuitive and robust multimodal robot control is the key toward human–robot collaboration
(HRC) for manufacturing systems. Multimodal robot control methods were introduced in …

One difficult problem of keyword spotting is how to miniaturize its memory footprint while
maintain a high precision. Although convolutional neural networks have shown to be …

Despite the recent successes of deep neural networks, it remains challenging to achieve
high precision keyword spotting task (KWS) on resource-constrained devices. In this study …

Keyword Spotting (KWS) is a significant branch of Automatic Speech Recognition (ASR) and
has been widely used in edge computing devices. The goal of KWS is to provide high …

Keyword spotting (KWS) enables speech-based user interaction and gradually becomes an
indispensable component of smart devices. Recently, end-to-end (E2E) methods have be …

Speech-based interfaces are convenient and intuitive, and therefore, strongly preferred by
Internet of Things (IoT) devices for human-computer interaction. Pre-defined keywords are …