17 citations · 17 across the 4 of their papers we have counts for
5 papers
On the long-term learning ability of LSTM LMs
Wim Boes, Robbe Van Rompaey, Lyan Verwimp +3
We inspect the long-term learning ability of Long Short-Term Memory language models (LSTM LMs) by evaluating a contextual extension based on the Continuous Bag-of-Words (CBOW) mode…
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…
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…
Language Models of Spoken Dutch
Lyan Verwimp, Joris Pelemans, Marieke Lycke +2
In Flanders, all TV shows are subtitled. However, the process of subtitling is a very time-consuming one and can be sped up by providing the output of a speech recognizer run on th…
Character-Word LSTM Language Models
Lyan Verwimp, Joris Pelemans, Hugo Van hamme +1
We present a Character-Word Long Short-Term Memory Language Model which both reduces the perplexity with respect to a baseline word-level language model and reduces the number of p…