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 …

This article focuses on the problem of query by example spoken term detection (QbE-STD)
in zero-resource scenario. State-of-the-art approaches primarily rely on dynamic time …

Keyword spotting--or wakeword detection--is an essential feature for hands-free operation of
modern voice-controlled devices. With such devices becoming ubiquitous, users might want …

In modern multilingual societies, there is a demand for multilingual Automatic Speech
Recognition (ASR) and Spoken Term Detection (STD). Multilingual Spoken Term Detection …

We propose to learn acoustic word embeddings with temporal context for query-by-example
(QbE) speech search. The temporal context includes the leading and trailing word …

Keyword spotting (KWS) is a task to recognize a keyword or a particular command in a
continuous audio stream, which can be effectively applied to a voice trigger system that …

Deep learning based approaches have greatly improved the performance of spoken
keyword spotting (KWS). However, KWS of different languages should have their own …

Pre-trained speech representations like wav2vec 2.0 are a powerful tool for automatic
speech recognition (ASR). Yet many endangered languages lack sufficient data for pre …

In this paper, a novel approach to unsupervised pattern discovery for speech signals is
proposed. Recently, we introduced an image processing method (IPM) that extracts the …

In the last decade, i-vector and Joint Factor Analysis (JFA) approaches to speaker modeling
have become ubiquitous in the area of automatic speaker recognition. Both of these …