Spoken keyword spotting (KWS) deals with the identification of keywords in audio streams
and has become a fast-growing technology thanks to the paradigm shift introduced by deep …

Keyword spotting is an important research field because it plays a key role in device wake-
up and user interaction on smart devices. However, it is challenging to minimize errors while …

In this paper, we propose a novel end-to-end user-defined keyword spotting method that
utilizes linguistically corresponding patterns between speech and text sequences. Unlike …

In recent years, Keyword Spotting (KWS) has become a crucial human–machine interface
for mobile devices, allowing users to interact more naturally with their gadgets by leveraging …

This study presents a novel zero-shot user-defined keyword spotting model that utilizes the
audio-phoneme relationship of the keyword to improve performance. Unlike the previous …

The development of keyword spotting (KWS) systems that are accurate in noisy conditions
remains a challenge. Towards this goal, in this paper we propose a novel training strategy …

Keyword spotting is the task of detecting a keyword in streaming audio. Conventional
keyword spotting targets predefined keywords classification, but there is growing attention in …

The Hopf oscillator is a nonlinear oscillator that exhibits limit cycle motion. This reservoir
computer utilizes the vibratory nature of the oscillator, which makes it an ideal candidate for …

Open-vocabulary keyword spotting (KWS) aims to detect arbitrary keywords from continuous
speech, which allows users to define their personal keywords. In this paper, we propose a …

In this paper, we propose a multilingual query-by-example keyword spotting (KWS) system
based on a residual neural network. The model is trained as a classifier on a multilingual …