SELD-TCN: Sound event localization & detection via temporal convolutional networks
The understanding of the surrounding environment plays a critical role in autonomous
robotic systems, such as self-driving cars. Extensive research has been carried out …
robotic systems, such as self-driving cars. Extensive research has been carried out …
A survey of artificial intelligence approaches in blind source separation
In various signal processing applications, such as audio signal recovery, the extraction of
desired signals from a mixture of other signals is a crucial task. To achieve superior …
desired signals from a mixture of other signals is a crucial task. To achieve superior …
Unsupervised training for deep speech source separation with Kullback-Leibler divergence based probabilistic loss function
In this paper, we propose a multi-channel speech source separation method with a deep
neural network (DNN) which is trained under the condition that no clean signal is available …
neural network (DNN) which is trained under the condition that no clean signal is available …
Speech and music separation approaches-a survey
With the growth of acoustic data in the development of multimedia tools, mobile phones and
the Internet of Multimedia Things (IoMT), recent studies exploit different models of machine …
the Internet of Multimedia Things (IoMT), recent studies exploit different models of machine …
[PDF][PDF] Mentoring-Reverse Mentoring for Unsupervised Multi-Channel Speech Source Separation.
Mentoring-reverse mentoring, which is a novel knowledge transfer framework for
unsupervised learning, is introduced in multi-channel speech source separation. This …
unsupervised learning, is introduced in multi-channel speech source separation. This …
[PDF][PDF] Efficient and Stable Adversarial Learning Using Unpaired Data for Unsupervised Multichannel Speech Separation.
This study presents a framework to enable efficient and stable adversarial learning of
unsupervised multichannel source separation models. When the paired data, ie, the mixture …
unsupervised multichannel source separation models. When the paired data, ie, the mixture …
Separating overlapping bat calls with a bi‐directional long short‐term memory network
K Zhang, T Liu, S Song, X Zhao, S Sun… - Integrative …, 2022 - Wiley Online Library
Acquiring clear acoustic signals is critical for the analysis of animal vocalizations.
Bioacoustics studies commonly face the problem of overlapping signals, which can impede …
Bioacoustics studies commonly face the problem of overlapping signals, which can impede …
Computer-resource-aware deep speech separation with a run-time-specified number of BLSTM layers
Recently, deep neural networks (DNNs) with multiple bidirectional long short term memory
(BLSTM) layers have been successfully applied to supervised multi-channel speech …
(BLSTM) layers have been successfully applied to supervised multi-channel speech …
Separation of alpha-stable random vectors
Source separation aims at decomposing a vector into additive components. This is often
done by first estimating source parameters before feeding them into a filtering method, often …
done by first estimating source parameters before feeding them into a filtering method, often …
Blind Noise Reduction for Speech Enhancement by Simulated Auditory Nerve Representations
A Yakovenko, A Antropov, G Malykhina - … 12, 2019, Proceedings, Part II 16, 2019 - Springer
Background and environmental noises negatively affect the quality of verbal communication
between humans as well as in human-computer interaction. However, this problem is …
between humans as well as in human-computer interaction. However, this problem is …