479 citations · 827 across the 35 of their papers we have counts for
8 papers · 1 filter
Nearest Neighbor Search-Based Bitwise Source Separation Using Discriminant Winner-Take-All Hashing
Sunwoo Kim, Minje Kim
We propose an iteration-free source separation algorithm based on Winner-Take-All (WTA) hash codes, which is a faster, yet accurate alternative to a complex machine learning model…
Incremental Binarization On Recurrent Neural Networks For Single-Channel Source Separation
Sunwoo Kim, Mrinmoy Maity, Minje Kim
This paper proposes a Bitwise Gated Recurrent Unit (BGRU) network for the single-channel source separation task. Recurrent Neural Networks (RNN) require several sets of weights wit…
A Dual-Staged Context Aggregation Method Towards Efficient End-To-End Speech Enhancement
Kai Zhen, Mi Suk Lee, Minje Kim
In speech enhancement, an end-to-end deep neural network converts a noisy speech signal to a clean speech directly in time domain without time-frequency transformation or mask esti…
Cascaded Cross-Module Residual Learning towards Lightweight End-to-End Speech Coding
Kai Zhen, Jongmo Sung, Mi Suk Lee +2
Speech codecs learn compact representations of speech signals to facilitate data transmission. Many recent deep neural network (DNN) based end-to-end speech codecs achieve low bitr…
Performance Optimization on Model Synchronization in Parallel Stochastic Gradient Descent Based SVM
Vibhatha Abeykoon, Geoffrey Fox, Minje Kim
Understanding the bottlenecks in implementing stochastic gradient descent (SGD)-based distributed support vector machines (SVM) algorithm is important in training larger data sets.…
Learning Everywhere: Pervasive Machine Learning for Effective High-Performance Computation
Geoffrey Fox, James A. Glazier, JCS Kadupitiya +10
The convergence of HPC and data-intensive methodologies provide a promising approach to major performance improvements. This paper provides a general description of the interaction…
Deep Autotuner: A Data-Driven Approach to Natural-Sounding Pitch Correction for Singing Voice in Karaoke Performances
Sanna Wager, George Tzanetakis, Cheng-i Wang +3
We describe a machine-learning approach to pitch correcting a solo singing performance in a karaoke setting, where the solo voice and accompaniment are on separate tracks. The prop…
AutoQ: Automated Kernel-Wise Neural Network Quantization
Qian Lou, Feng Guo, Lantao Liu +2
Network quantization is one of the most hardware friendly techniques to enable the deployment of convolutional neural networks (CNNs) on low-power mobile devices. Recent network qu…