A nearly end-to-end deep learning approach to fault diagnosis of wind turbine gearboxes under nonstationary conditions
Fault diagnosis of wind turbine gearboxes is crucial in ensuring wind farms' reliability and
safety. However, nonstationary working conditions, such as load change or speed …
safety. However, nonstationary working conditions, such as load change or speed …
Audiodec: An open-source streaming high-fidelity neural audio codec
A good audio codec for live applications such as telecommunication is characterized by
three key properties:(1) compression, ie the bitrate that is required to transmit the signal …
three key properties:(1) compression, ie the bitrate that is required to transmit the signal …
Low bit-rate speech coding with VQ-VAE and a WaveNet decoder
In order to efficiently transmit and store speech signals, speech codecs create a minimally
redundant representation of the input signal which is then decoded at the receiver with the …
redundant representation of the input signal which is then decoded at the receiver with the …
Wavecrn: An efficient convolutional recurrent neural network for end-to-end speech enhancement
Due to the simple design pipeline, end-to-end (E2E) neural models for speech
enhancement (SE) have attracted great interest. In order to improve the performance of the …
enhancement (SE) have attracted great interest. In order to improve the performance of the …
End-to-end optimized speech coding with deep neural networks
S Kankanahalli - … Conference on Acoustics, Speech and Signal …, 2018 - ieeexplore.ieee.org
Modern compression algorithms are often the result of laborious domain-specific research;
industry standards such as MP3, JPEG, and AMR-WB took years to develop and were …
industry standards such as MP3, JPEG, and AMR-WB took years to develop and were …
Low latency and sparse computing spiking neural networks with self-driven adaptive threshold plasticity
Spiking neural networks (SNNs) have captivated the attention worldwide owing to their
compelling advantages in low power consumption, high biological plausibility, and strong …
compelling advantages in low power consumption, high biological plausibility, and strong …
Cascaded cross-module residual learning towards lightweight end-to-end speech coding
Speech codecs learn compact representations of speech signals to facilitate data
transmission. Many recent deep neural network (DNN) based end-to-end speech codecs …
transmission. Many recent deep neural network (DNN) based end-to-end speech codecs …
Fast and robust learning in spiking feed-forward neural networks based on intrinsic plasticity mechanism
A Zhang, H Zhou, X Li, W Zhu - Neurocomputing, 2019 - Elsevier
In this paper, the computational performance of a Spiking Feed-forward Neural Network
(SFNN) is investigated based on a brain-inspired Intrinsic Plasticity (IP) mechanism, which is …
(SFNN) is investigated based on a brain-inspired Intrinsic Plasticity (IP) mechanism, which is …
Auditory perception architecture with spiking neural network and implementation on FPGA
B Deng, Y Fan, J Wang, S Yang - Neural Networks, 2023 - Elsevier
Spike-based perception brings up a new research idea in the field of neuromorphic
engineering. A high-performance biologically inspired flexible spiking neural network (SNN) …
engineering. A high-performance biologically inspired flexible spiking neural network (SNN) …
Cognitive speech coding: examining the impact of cognitive speech processing on speech compression
Speech coding is a field in which compression paradigms have not changed in the last 30
years. Speech signals are most commonly encoded with compression methods that have …
years. Speech signals are most commonly encoded with compression methods that have …