Dietary behaviour is an important lifestyle aspect and directly related to long-term health. We present an approach to detect eating and drinking intake cycles from body-worn sensors. Information derived from the sensors are considered as abstract activity events and a sequence modelling is applied utilising probabilistic context-free grammars. Different grammar models are discussed and applied...

In this work we propose methods to label probabilistic synchronous context-free grammar (PSCFG) rules using only word tags, generated by either part-of-speech analysis or unsupervised word class induction. The proposals range from simple tag-combination schemes to a phrase clustering model that can incorporate an arbitrary number of features. Our models improve translation quality over the sing...

We generalize Solomonoff’s stochastic context-free grammar induction method to context-sensitive grammars, and apply it to transfer learning problem by means of an efficient update algorithm. The stochastic grammar serves as a guiding program distribution which improves future probabilistic induction approximations by learning about the training sequence of problems. Stochastic grammar is updat...

Predicting the secondary structure of RNA molecules from the knowledge of the primary structure (the sequence of bases) is still a challenging task. There are algorithms that provide good results e.g. based on the search for an energetic optimal configuration. However the output of such algorithms does not always give the real folding of the molecule and therefore a feature to judge the reliabi...

Second-order abstract categorial grammars (de Groote 2001) and hyperedge replacement grammars (see Engelfriet 1997) are two natural ways of generalizing “context-free” grammar formalisms for string and tree languages. It is known that the string generating power of both formalisms is equivalent to (non-erasing) multiple context-free grammars (Seki et al. 1991) or linear context-free rewriting s...

In this paperwe consider the problemof efficient computation of cross-moments of a vector randomvariable represented by a stochastic context-free grammar. Two types of cross-moments are discussed. The sample space of the first one is the set of all derivations of the context-free grammar, and the sample space of the second one is the set of all derivations which generate a string belonging to t...

Recently, the use of syntax has very effectively improved machine translation (MT) quality in many text translation tasks. However, using syntax in speech translation poses additional challenges because of disfluencies and other spoken language phenomena, and of errors introduced by automatic speech recognition (ASR). In this paper, we investigate the effect of using syntax in a large-scale aud...

Tree substitution grammars (TSGs) are a compelling alternative to context-free grammars for modelling syntax. However, many popular techniques for estimating weighted TSGs (under the moniker of Data Oriented Parsing) suffer from the problems of inconsistency and over-fitting. We present a theoretically principled model which solves these problems using a Bayesian non-parametric formulation. Our...

A derivation step in a Graph Interpolation Grammar has the effect of scanning an input token. This feature, which aims at emulating the incrementality of the natural parser, restricts the formal power of GIGs. This contrasts with the fact that the derivation mechanism involves a context-sensitive device similar to tree adjunction in TAGs. The combined effect of input-driven derivation and restr...

By a “tree-bank grammar” we mean a context-free grammar created by reading the production rules directly from hand-parsed sentences in a tree bank. Common wisdom has it that such grammars do not perform we& though we know of no published data on the issue. The primary purpose of this paper is to show that the common wisdom is wrong. In particular, we present results on a tree-bank grammar based...