21 citations · 154 across the 60 of their papers we have counts for
5 papers · 1 filter
Information-Weighted Neural Cache Language Models for ASR
Lyan Verwimp, Joris Pelemans, Hugo Van hamme +1
Neural cache language models (LMs) extend the idea of regular cache language models by making the cache probability dependent on the similarity between the current context and the…
Memory Time Span in LSTMs for Multi-Speaker Source Separation
Jeroen Zegers, Hugo Van hamme
With deep learning approaches becoming state-of-the-art in many speech (as well as non-speech) related machine learning tasks, efforts are being taken to delve into the neural netw…
Multi-scenario deep learning for multi-speaker source separation
Jeroen Zegers, Hugo Van hamme
Research in deep learning for multi-speaker source separation has received a boost in the last years. However, most studies are restricted to mixtures of a specific number of speak…
State Gradients for RNN Memory Analysis
Lyan Verwimp, Hugo Van hamme, Vincent Renkens +1
We present a framework for analyzing what the state in RNNs remembers from its input embeddings. Our approach is inspired by backpropagation, in the sense that we compute the gradi…
Capsule Networks for Low Resource Spoken Language Understanding
Vincent Renkens, Hugo Van hamme
Designing a spoken language understanding system for command-and-control applications can be challenging because of a wide variety of domains and users or because of a lack of trai…