Name Strategy: Its Existence and Implications

It is argued that colour name strategy, object name strategy, and chunking strategy in memory are all aspects of the same general phenomena, called stereotyping, and this in turn is an example of a know-how representation. Such representations are argued to have their origin in a principle called the minimum duplication of resources. For most the subsequent discussions existence of colour name strategy suffices. It is pointed out that the Berlin†- Kay† universal partial ordering of colours and the frequency of traffic accidents classified by colour are surprisingly similar; a detailed analysis is not carried out as the specific colours recorded are not identical. Some consequences of the existence of a name strategy for the philosophy of language and mathematics are discussed: specifically it is argued that in accounts of truth and meaning it is necessary throughout to use real numbers as opposed to bi-valent quantities; and also that the concomitant label associated with sentences should not be of unconditional truth, but rather several real-valued quantities associated with visual communication. The implication of real-valued truth quantities is that the Continuum Hypothesis of pure mathematics is side-stepped, because real valued quantities occur ab initio. The existence of name strategy shows that thought/sememes and talk/phonemes can be separate, and this vindicates the assumption of thought occurring before talk used in psycho-linguistic speech production models.

Evaluating syntax-driven approaches to phrase extraction for MT

In this paper, we examine a number of different phrase segmentation approaches for Machine Translation and how they perform when used to supplement the translation model of a phrase-based SMT system. This work represents a summary of a number of years of research carried out at Dublin City University in which it has been found that improvements can be made using hybrid translation models. However, the level of improvement achieved is dependent on the amount of training data used. We describe the various approaches to phrase segmentation and combination explored, and outline a series of experiments investigating the relative merits of each method

Towards Understanding Egyptian Arabic Dialogues

Labelling of user's utterances to understanding his attends which called Dialogue Act (DA) classification, it is considered the key player for dialogue language understanding layer in automatic dialogue systems. In this paper, we proposed a novel approach to user's utterances labeling for Egyptian spontaneous dialogues and Instant Messages using Machine Learning (ML) approach without relying on any special lexicons, cues, or rules. Due to the lack of Egyptian dialect dialogue corpus, the system evaluated by multi-genre corpus includes 4725 utterances for three domains, which are collected and annotated manually from Egyptian call-centers. The system achieves F1 scores of 70. 36% overall domains.Comment: arXiv admin note: substantial text overlap with arXiv:1505.0308