Sentence examples for language modelling from inspiring English sources

In statistical language modelling, data sparseness is particularly acute in the case of morphologically rich languages.

Modern speech recognition systems require implementation of the acoustic and language modelling [2].

Our contributions are in five areas, namely tracking, features, signer dependency, visual modelling and language modelling.

Further use of linguistic knowledge indeed improves the recognition rate of the system as shown with the OC data, but the improvement by language modelling diminishes the impact of articulation and voice on the WR.

In recent years, as in many other NLG applications, surface realisation systems have successfully relied upon statistical methods ranging from language modelling techniques [2, 3] to full-blown probabilistic generation-space models [4] and grammar acquisition [5].

In the former, the truth predicate Tr for the relevant formal language, modelling the behaviour of truth in English, is simply characterized by the unrestricted T-schema, which, as stressed by many philosophers, is an overwhelmingly intuitive — one may dare say, 'analytic' — principle concerning truth.

The recurrent neural network language model (RNNLM) has shown significant promise for statistical language modeling.

The perturbation approach adds robustness to the language modeling.

In this paper, we have introduced a modified recurrent neural network-based language model for language modeling.

Intrinsic information has been largely overlooked by language modeling research.

A planning language modeled by the sets of world-plan pairs would serve very well.