Handbook of the International Phonetic Association: A Guide to the Use of the International Phonetic Alphabet

English Phonetics and Phonology

We present Hover Widgets, a new technique for increasing the capabilities of pen-based interfaces. Hover Widgets are implemented by using the pen movements above the display surface, in the tracking state. Short gestures while hovering, followed by a pen down, access the Hover Widgets, which can be used to activate localized interface widgets. By using the tracking state movements, Hover Widgets create a new command layer which is clearly distinct from the input layer of a pen interface. In a formal experiment Hover Widgets were found to be faster than a more traditional command activation technique, and also reduced errors due to divided attention.

/pdf/hover-widgets-using-the-tracking-state-to-extend-the-1qenazn44b.pdf

Hover widgets: using the tracking state to extend the capabilities of pen-operated devices

Provided is multi-stroke marking menu techniques that increase menu breath over an eight-item limit of some orientation-based marking menus. Zone and polygon menus can be provided wherein the breadth can be increased by a factor of about two or more while providing quick selection and maintaining selection accuracy. Various geometric attributes can be analyzed to determine a selection stroke. These attributes can include orientation, position, and/or length of each stroke. Hybrid techniques are also disclosed that further increase menu breadth and performance.

Position-based multi-stroke marking menus

Review of "Lecture on contemporary syntactic theories

The invention refers to a computer-based system for the acquisition, analysis, and authentication of the handwritten signature. The person that performs a handwritten signature performs a series of three-dimensional movements with a plane graphical finality. The movements generate kinetic information perceived by the special pen that the signature is performed with (the writing and digital acquisition device for the primary bio-kinetic information). The information, concordant to the afferent bio-kinetic pattern, is collected by the included MEMS type acceleration sensors in the pen. The system continues to analyze the generated information (the signals) and it determines the dynamic-biometrical characteristics, based upon the biometrical dimension of the information. The characteristics are transformed in data vectors and invariants that are stored in a database. Based on algorithm type methods, the system performs the required comparisons between the spatial kinetics of the specimens and the kinetics of the entrances and obtains distance-type answers. In statistical terms, the results are related to the entire subject database, by interpreting and sampling methods.

System and methods of acquisition, analysis and authentication of the handwritten signature

The Multi-word Expressions (MWE) treatment is a very difficult problem for the Natural Language Processing in general and for Machine Translation in particular. This is true because each word of a MWE can have a specific meaning but the expression can have a totally different meaning both in source and in target language of a translation. The things are complicated also by the fact that the source expression can appear in the source text under a very different form from its form in a bilingual MWE dictionary (it can have some inflections) and, most of all, it can have some extensions (some MWE words can have associated new words that do not belong to the MWE). The paper show how this kind of problems can be treated and solved using Generative Dependency Grammar with Features.

Multiword Expression Translation Using Generative Dependency Grammar

In some embodiments, a linguistic application exploits a linguistic knowledgebase (LKB) including, among others, lexicon data, inflection form data, and syntax data for a natural language such as English or Romanian. The application employs a set modules including a word retriever, a form generator, and a syntax checker, which are interconnected to perform a number of higher-level text-processing operations such as synthetic and analytic annotation, lemmatizing, spell checking, and grammar checking.

Systems and methods for natural language processing including morphological analysis, lemmatizing, spell checking and grammar checking

This document presents a new kind of grammars: the Generative Dependency Grammar (GDG) and GDG with Feature Structure (FS) represented as Attribute Value Tree (AVT). This type of grammars is based on dependency trees (DT) and a generative process. GDG will eliminate some issues of Dependency Grammars DG (for example the missing of phrasal categories) and Generative Grammars GG (the problem of discontinuous structures) and will merge the advantages of the two types of grammar (GG — the representation of phrasal categories; GDG — the handling of discontinuous structures as gaps and non projective constructions). We present the generation process and the unification in GDG. Some properties of AVT and a logical representation of AVT are presented too. GDG is useful in grammar representations for natural language understanding, machine translation and data retrieval.

/pdf/natural-language-understanding-using-generative-dependency-3g1c6ww97f.pdf

Natural Language Understanding Using Generative Dependency Grammar

In some embodiments, linguistic knowledge bases including multiword lexicon entries belonging to various natural languages are generated and maintained. Multiword lexicon entries include representations of multiword expressions (e.g. composite words such as “expectation value”, verbal phrases such as “to stumble upon”, and idiomatic phrases such as “to hit the nail on the head”), and multiword inflection templates (e.g. “more adjective” as a symbolic representation for the comparative form of adjectives). A representation of a multiword lexicon entry, including a dependency tree and/or an attribute-value tree, is displayed within a graphical user interface, allowing a user to verify, update, and correct lexical data. Computer-readable encodings (e.g. XML) of dependency tree and/or attribute-value tree data are saved as part of each lexicon entry.

Stefan Diaconescu

Papers

System and methods of acquisition, analysis and authentication of the handwritten signature

Multiword Expression Translation Using Generative Dependency Grammar

Systems and methods for natural language processing including morphological analysis, lemmatizing, spell checking and grammar checking

Natural Language Understanding Using Generative Dependency Grammar

Systems and methods for managing a complex lexicon comprising multiword expressions and multiword inflection templates