Search Results for author:
Found 9 papers, 2 papers with code
On the long-term learning ability of LSTM LMs
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) model for both sentence- and discourse-level LSTM LMs and by analyzing its performance.
Information-Weighted Neural Cache Language Models for ASR
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 context of the words in the cache.
State Gradients for RNN Memory Analysis
We present a framework for analyzing what the state in RNNs remembers from its input embeddings.
Language Models of Spoken Dutch
One model is trained on all available data (46M word tokens), but we also trained models on a specific type of TV show or domain/topic.
Character-Word LSTM Language Models
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 parameters of the model.
SCALE: A Scalable Language Engineering Toolkit
In this paper we present SCALE, a new Python toolkit that contains two extensions to n-gram language models.
Speech Recognition Web Services for Dutch
In this paper we present 3 applications in the domain of Automatic Speech Recognition for Dutch, all of which are developed using our in-house speech recognition toolkit SPRAAK.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
