Spectral sub-bands do not portray the same perceptual relevance. In audi...
With the advances in deep learning, speech enhancement systems benefited...
Low and ultra-low-bitrate neural speech coding achieves unprecedented co...
In the stereo-to-multichannel upmixing problem for music, one of the mai...
With the recent advancements of data driven approaches using deep neural...
In this paper, we present a blockwise optimization method for masking-ba...
The task of manipulating the level and/or effects of individual instrume...
An autoencoder-based codec employs quantization to turn its bottleneck l...
In realistic speech enhancement settings for end-user devices, we often
...
This paper presents a novel zero-shot learning approach towards personal...
Training personalized speech enhancement models is innately a no-shot
le...
Speech enhancement systems can show improved performance by adapting the...
This work presents a scalable and efficient neural waveform codec (NWC) ...
Conventional audio coding technologies commonly leverage human perceptio...
This work explores how self-supervised learning can be universally used ...
In this paper, we investigate a deep learning approach for speech denois...
Speech enhancement tasks have seen significant improvements with the adv...
Scalability and efficiency are desired in neural speech codecs, which
su...
We introduce a data-driven approach to automatic pitch correction of sol...
We propose an iteration-free source separation algorithm based on
Winner...
This paper proposes a Bitwise Gated Recurrent Unit (BGRU) network for th...
In speech enhancement, an end-to-end deep neural network converts a nois...
In speech enhancement, an end-to-end deep neural network converts a nois...
Speech codecs learn compact representations of speech signals to facilit...
Understanding the bottlenecks in implementing stochastic gradient descen...
The convergence of HPC and data-intensive methodologies provide a promis...
In this paper, we propose a hierarchical deep reinforcement learning
(DR...
We describe a machine-learning approach to pitch correcting a solo singi...
In this paper, we present a machine-learning approach to pitch correctio...
We present a psychoacoustically enhanced cost function to balance networ...
We present DeepPicar, a low-cost deep neural network based autonomous ca...
This paper proposes an efficient bitwise solution to the single-channel
...
Based on the assumption that there exists a neural network that efficien...
Monaural source separation is important for many real world applications...