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This report explores the question of compatibility between annotation projects including translating annotation formalisms to each other or to common forms. Compatibility issues are crucial for systems that use the results of multiple annotation projects. We hope that this report will begin a concerted effort in the field to track the compatibility of annotation schemes for part of speech tagging, time annotation, treebanking, role labeling and other phenomena.
We investigate methods to improve the recall in coreference resolution by also trying to resolve those definite descriptions where no earlier mention of the referent shares the same lexical head (coreferent bridging). The problem, which is notably harder than identifying coreference relations among mentions which have the same lexical head, has been tackled with several rather different approaches, and we attempt to provide a meaningful classification along with a quantitative comparison. Based on the different merits of the methods, we discuss possibilities to improve them and show how they can be effectively combined.
Eins der signifikanten Probleme in der maschinellen Übersetzung japanische in deutsche Sprache ist die fehlende Information und Definitheit im japanischen Analyse-Output. Eine effiziente Lösung dieses Problems ist es, die Suche nach der relevanten Information in den Transfer zu integrieren. Transferregeln werden mit Präferenzregeln und Default-Regeln kombiniert. Dadurch wird Information über lexikalische Restriktionen der Zielsprache, über die Domäne und über den Diskurs zugänglich.
The goal of our current project is to build a system that can learn to imitate a version of a spoken utterance using an articulatory speech synthesiser. The approach is informed and inspired by knowledge of early infant speech development. Thus we expect our system to reproduce and exploit the utility of infant behaviours such as listening, vocal play, babbling and word imitation. We expect our system to develop a relationship between the sound-making capabilities of its vocal tract and the phonetic/phonological structure of imitated utterances. At the heart of our approach is the learning of an inverse model that relates acoustic and motor representations of speech. The acoustic to auditory mappings uses an auditory filter bank and a self-organizing phase of learning. The inverse model from auditory to vocal tract control parameters is estimated using a babbling phase, in which the vocal tract is essentially driven in a random manner, much like the babbling phase of speech acquisition in infants. The complete system can be used to imitate simple utterances through a direct mapping from sound to control parameters. Our initial results show that this procedure works well for sounds generated by its own voice. Further work is needed to build a phonological control level and achieve better performance with real speech.
The author presents MASSY, the MODULAR AUDIOVISUAL SPEECH SYNTHESIZER. The system combines two approaches of visual speech synthesis. Two control models are implemented: a (data based) di-viseme model and a (rule based) dominance model where both produce control commands in a parameterized articulation space. Analogously two visualization methods are implemented: an image based (video-realistic) face model and a 3D synthetic head. Both face models can be driven by both the data based and the rule based articulation model.
The high-level visual speech synthesis generates a sequence of control commands for the visible articulation. For every virtual articulator (articulation parameter) the 3D synthetic face model defines a set of displacement vectors for the vertices of the 3D objects of the head. The vertices of the 3D synthetic head then are moved by linear combinations of these displacement vectors to visualize articulation movements. For the image based video synthesis a single reference image is deformed to fit the facial properties derived from the control commands. Facial feature points and facial displacements have to be defined for the reference image. The algorithm can also use an image database with appropriately annotated facial properties. An example database was built automatically from video recordings. Both the 3D synthetic face and the image based face generate visual speech that is capable to increase the intelligibility of audible speech.
Other well known image based audiovisual speech synthesis systems like MIKETALK and VIDEO REWRITE concatenate pre-recorded single images or video sequences, respectively. Parametric talking heads like BALDI control a parametric face with a parametric articulation model. The presented system demonstrates the compatibility of parametric and data based visual speech synthesis approaches.
MED (Media EDitor) is a program designed to facilitate the transcription of digitized soundfiles into textfiles. It was written by Hans Drexler and Daan Broeder, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands. [...] The aim of MED is to facilitate the transcription of sound into text using a single program. It works on the principle of the coexistence and interaction of two basic elements, the waveform display window and the text window. [...] This means that you no longer need to use both a sound editor and a word processor at the same time in order to transcribe digitized speech files. Instead, you can directly type the sound you hear (and see) via MED into the text window. Furthermore, you can directly link sound portions of the waveform display window to text portions of the text window, so that you can easily locate and listen to the original source of your transcription once the links have been set. In this function the waveform display window and the text window virtually interact with each other.
The Conference on Computational Natural Language Learning features a shared task, in which participants train and test their learning systems on the same data sets. In 2007, as in 2006, the shared task has been devoted to dependency parsing, this year with both a multilingual track and a domain adaptation track. In this paper, we define the tasks of the different tracks and describe how the data sets were created from existing treebanks for ten languages. In addition, we characterize the different approaches of the participating systems, report the test results, and provide a first analysis of these results.
In this paper, I revisit the arguments against the use of fuzzy logic in linguistics (or more generally, against a truth-functional account of vagueness). In part, this is an exercise to explain to fuzzy logicians why linguists have shown little interest in their research paradigm. But, the paper contains more than this interdisciplinary service effort that I started out on: In fact, this seems an opportune time for revisiting the arguments against fuzzy logic in linguistics since three recent developments affect the argument. First, the formal apparatus of fuzzy logic has been made more general since the 1970s, specifically by Hajek [6], and this may make it possible to define operators in a way to make fuzzy logic more suitable for linguistic purposes. Secondly, recent research in philosophy has examined variations of fuzzy logic ([18, 19]). Since the goals of linguistic semantics seem sometimes closer to those of some branches of philosophy of language than they are to the goals of mathematical logic, fuzzy logic work in philosophy may mark the right time to reexamine fuzzy logic from a linguistic perspective as well. Finally, the reasoning used to exclude fuzzy logic in linguistics has been tied to the intuition that p and not p is a contradiction. However, this intuition seems dubious especially when p contains a vague predicate. For instance, one can easily think of circumstances where 'What I did was smart and not smart.' or 'Bea is both tall and not tall.' don’t sound like senseless contradictions. In fact, some recent experimental work that I describe below has shown that contradictions of classical logic aren’t always felt to be contradictory by speakers. So, it is important to see to what extent the argument against fuzzy logic depends on a specific stance on the semantics of contradictions. In sum then, there are three good reasons to take another look at fuzzy logic for linguistic purposes.
The Child Language Data Exchange System (CHILDES) consists of Codes for the Human Analysis of Transcripts (CHAT), Computerized Language Analysis (CLAN), and a database. There is also an online manual which includes the CHILDES bibliography, the database, and the CHAT conventions as well as the CLAN instructions. The first three parts of this paper concern the CHAT format of transcription, grammatical coding, and analyzing transcripts by using the CLAN programs. The fourth part shows examples of transcribed and coded data.