In this paper, we propose a joint generative and contrastive representat...
In this paper, we propose an effective sound event detection (SED) metho...
In this paper, we present a high-performance and light-weight deep learn...
Transformers have recently dominated the ASR field. Although able to yie...
In this paper, we evaluate various deep learning frameworks for detectin...
Recently, end-to-end (E2E) speech recognition has become popular, since ...
Recently, online end-to-end ASR has gained increasing attention. However...
Rear-end collision accounts for around 8
with the failure to notice or r...
End-to-end speech recognition has become popular in recent years, since ...
This paper presents a novel Dialect Identification (DID) system develope...
Although large annotated sleep databases are publicly available, and mig...
Acoustic scenes are rich and redundant in their content. In this work, w...
Due to the variability in characteristics of audio scenes, some can natu...
We propose a multi-label multi-task framework based on a convolutional
r...
This paper presents a methodology for early detection of audio events fr...
We introduce a new learned descriptor for audio signals which is efficie...