Recurrent neural network language models (RNNLM) have become an increasingly popular
choice for state-of-the-art speech recognition systems due to their inherently strong …

Disclosed embodiments include methods and systems for symbolic correction in human-
machine interfaces that comprise (a) implementing a language model;(b) implementing a …

An important part of the language modelling problem for automatic speech recognition
(ASR) systems, and many other related applications, is to appropriately model long-distance …

Neural network language models (NNLM) have become an increasingly popular choice for
large vocabulary continuous speech recognition (LVCSR) tasks, due to their inherent …

Language models (LMs) are often constructed by building multiple individual component
models that are combined using context independent interpolation weights. By tuning these …

Code-switching language modeling is challenging due to statistics of each individual
language, as well as statistics of cross-lingual language are insufficient. To compensate for …

State-of-the-art large vocabulary continuous speech recognition (LVCSR) systems often
combine outputs from multiple sub-systems that may even be developed at different sites …

Mandarin Chinese is based on characters which are syllabic in nature and morphological in
meaning. All spoken languages have syllabiotactic rules which govern the construction of …

Natural languages are known for their expressive richness. Many sentences can be used to
represent the same underlying meaning. Only modelling the observed surface word …

Abstract Hidden Markov models (HMMs) have been the mainstream acoustic modelling
approach for state-of-the-art automatic speech recognition (ASR) systems over the past few …