05 Fakultät Informatik, Elektrotechnik und Informationstechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6
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Item Open Access Task-oriented specialization techniques for entity retrieval(2020) Glaser, Andrea; Kuhn, Jonas (Prof. Dr.)Finding information on the internet has become very important nowadays, and online encyclopedias or websites specialized in certain topics offer users a great amount of information. Search engines support users when trying to find information. However, the vast amount of information makes it difficult to separate relevant from irrelevant facts for a specific information need. In this thesis we explore two areas of natural language processing in the context of retrieving information about entities: named entity disambiguation and sentiment analysis. The goal of this thesis is to use methods from these areas to develop task-oriented specialization techniques for entity retrieval. Named entity disambiguation is concerned with linking referring expressions (e.g., proper names) in text to their corresponding real world or fictional entity. Identifying the correct entity is an important factor in finding information on the internet as many proper names are ambiguous and need to be disambiguated to find relevant information. To that end, we introduce the notion of r-context, a new type of structurally informed context. This r-context consists of sentences that are relevant to the entity only to capture all important context clues and to avoid noise. We then show the usefulness of this r-context by performing a systematic study on a pseudo-ambiguity dataset. Identifying less known named entities is a challenge in named entity disambiguation because usually there is not much data available from which a machine learning algorithm can learn. We propose an approach that uses an aggregate of textual data about other entities which share certain properties with the target entity, and learn information from it by using topic modelling, which is then used to disambiguate the less known target entity. We use a dataset that is created automatically by exploiting the link structure in Wikipedia, and show that our approach is helpful for disambiguating entities without training material and with little surrounding context. Retrieving the relevant entities and information can produce many search results. Thus, it is important to effectively present the information to a user. We regard this step beyond the entity retrieval and employ sentiment analysis, which is used to analyze opinions expressed in text, in the context of effectively displaying information about product reviews to a user. We present a system that extracts a supporting sentence, a single sentence that captures both the sentiment of the author as well as a supportingfact. This supporting sentence can be used to provide users with an easy way to assess information in order to make informed choices quickly. We evaluate our approach by using the crowdsourcing service Amazon Mechanical Turk.Item Open Access German clause-embedding predicates : an extraction and classification approach(2010) Lapshinova-Koltunski, Ekaterina; Heid, Ulrich (Prof. Dr. phil. habil.)This thesis describes a semi-automatic approach to the analysis of subcategorisation properties of verbal, nominal and multiword predicates in German. We semi-automatically classify predicates according to their subcategorisation properties by means of extracting them from German corpora along with their complements. In this work, we concentrate exclusively on sentential complements, such as dass, ob and w-clauses, although our methods can be also applied for other complement types. Our aim is not only to extract and classify predicates but also to compare subcategorisation properties of morphologically related predicates, such as verbs and their nominalisations. It is usually assumed that subcategorisation properties of nominalisations are taken over from their underlying verbs. However, our tests show that there exist different types of relations between them. Thus, we review subcategorisation properties of morphologically related words and analyse their correspondences and differences. For this purpose, we elaborate a set of semi-automatic procedures, which allow us not only to classify extracted units according to their subcategorisation properties, but also to compare the properties of verbs and their nominalisations, which occur both freely in corpora and within a multiword expression. The lexical data are created to serve symbolic NLP, especially large symbolic grammars for deep processing, such as HPSG or LFG, cf. work in the LinGO project (Copestake et al. 2004) and the Pargram project (Butt et al. 2002). HPSG and LFG need detailed linguistic knowledge. Besides that, subcategorisation iformation can be applied in applications for IE, cf. (Surdeanu et al. 2003). Moreover, this information is necessary for linguistic, lexicographic, SLA and translation work. Our extraction and classification procedures are precision-oriented, which means that we focus on high accuracy of our extraction and classification results. High precision is opposed to completeness, which is compensated by the application of extraction procedures on larger corpora.Item Open Access The perfect time span : on the present perfect in German, Swedish and English(2006) Rothstein, Björn Michael; Kamp, Hans (Prof. Dr. h.c. PhD)This study proposes a discourse based approach to the present perfect in German, Swedish and English. It is argued that the present perfect is best analysed by applying an ExtendedNow-approach. It introduces a perfect time span in which the event time expressed by the present perfect is contained. The present perfects in these languages differ with respect to the boundaries of perfect time span. In English, the right boundary is identical to the point of speech, in Swedish it can be either at or after the moment of speech and in German it can also be before the moment of speech. The left boundary is unspecified. The right boundary is set by context.Item Open Access Segmental factors in language proficiency : degree of velarization, coarticulatory resistance and vowel formant frequency distribution as a signature of talent(2011) Baumotte, Henrike; Dogil, Grzegorz (Prof. Dr.)The present PhD proposes a reason for German native speakers of various proficiency levels and multiple English varieties producing their L2 English with different degrees of a foreign accent. The author took into account phonetic measurements to investigate the degree of velarization and coarticulation or coarticulatory resistance respectively in German and English, taking non-words and natural language stimuli. To get an impression of the differences between the productions of proficient, average and less proficient speakers in German and English, the mean F2 and Fv values in /ə/ before /l/ and in /l/ were calculated, for then comparing the degree of velarization in /əlV/ non-word sequences with each other. Proficient speakers gained lower formant frequencies for F2 and Fv in /ə/ than less proficient speakers, i.e. proficient speakers velarized more than less proficient speakers. Within the comparisons with respect to coarticulation or coarticulatory resistance results respectively the difference values for F2 and F2' out of /ə/ in /əleɪ/ vs. /əlu:/, /əly/ vs. /əleɪ/ and /əly/ vs. /əlaɪ/ were created. In the whole series of measurements, an overwhelming trend for proficient speakers being more coarticulatory resistant, i.e. velarizing more, and more precisely pronouncing English vowel characteristics than less proficient speakers was present, while average speakers did not continuously behave according to prediction, as a result of being sometimes “worse” than less proficient speakers. On the basis of Díaz et al. (2008) who pled for pre-existing individual differences in phonetic discrimination ability which enormously influence the achievement of a foreign sound system, it is claimed for a derivation of foreign language from native phonetic abilities.Item Open Access Computational modelling of coreference and bridging resolution(2019) Rösiger, Ina; Kuhn, Jonas (Prof. Dr.)Item Open Access Modeling the interface between morphology and syntax in data-driven dependency parsing(2016) Seeker, Wolfgang; Kuhn, Jonas (Prof. Dr.)When people formulate sentences in a language, they follow a set of rules specific to that language that defines how words must be put together in order to express the intended meaning. These rules are called the grammar of the language. Languages have essentially two ways of encoding grammatical information: word order or word form. English uses primarily word order to encode different meanings, but many other languages change the form of the words themselves to express their grammatical function in the sentence. These languages are commonly subsumed under the term morphologically rich languages. Parsing is the automatic process for predicting the grammatical structure of a sentence. Since grammatical structure guides the way we understand sentences, parsing is a key component in computer programs that try to automatically understand what people say and write. This dissertation is about parsing and specifically about parsing languages with a rich morphology, which encode grammatical information in the form of words. Today’s parsing models for automatic parsing were developed for English and achieve good results on this language. However, when applied to other languages, a significant drop in performance is usually observed. The standard model for parsing is a pipeline model that separates the parsing process into different steps, in particular it separates the morphological analysis, i.e. the analysis of word forms, from the actual parsing step. This dissertation argues that this separation is one of the reasons for the performance drop of standard parsers when applied to other languages than English. An analysis is presented that exposes the connection between the morphological system of a language and the errors of a standard parsing model. In a second series of experiments, we show that knowledge about the syntactic structure of sentence can support the prediction of morphological information. We then argue for an alternative approach that models morphological analysis and syntactic analysis jointly instead of separating them. We support this argumentation with empirical evidence by implementing two parsers that model the relationship between morphology and syntax in two different but complementary ways.Item Open Access The German boundary tones: categorical Perception, perceptual magnets, and the perceptual reference space(2012) Schneider, Katrin; Dogil, Grzegorz (Prof. Dr.)This thesis experimentally analyzes the perception of prosodic categories in German, using the two German boundary tones L% and H% postulated by German phonology. These two boundary tone categories were selected because they constitute the least disputed tonal contrast. In many languages, in German as well, the contrast between the low (L%) and the high (H%) boundary tone corresponds to a contrast in sentence mode. The low boundary tone is interpreted as a statement and the high boundary tone as a question. For all experiments presented in this thesis it is hypothesized that the different perception of L% and H% as statement versus question, respectively, can be attributed to a contrast between two prosodic categories, i.e. to Categorical Perception. The basis for this hypothesis is the observation that the sentence mode of a syntactically ambiguous utterance can only be determined by the height of its boundary tone. Assuming the existence of the two proposed boundary tone categories two experimental designs that can be used to confirm categories, perceptual differences inside a category or perceptual differences between categories are presented. These two designs are the test for the Categorical Perception (CP) and the test for the Perceptual Magnet Effect (PME). Originally, both designs were developed to examine perceptual differences in the segmental domain, especially for the evaluation of phoneme categories. Categorical Perception is confirmed when the boundary between these two categories corresponds to the point at which the discrimination performance between two adjacent stimuli is best. If for two speech events the Categorical Perception test is successful then these two events will be confirmed as being categories of the respective language. A Perceptual Magnet Effect includes a warping of the perceptual space towards a prototype of the respective category. Such a warping does not occur towards a non-prototype of the same category. The result of the warping is a significantly lower discrimination performance around the prototype, i.e. the prototype is not or only hard to discriminate from a adjacent stimulus. Such a warping is not found around a non-prototype, although the acoustic difference between a stimulus and the non-prototype is comparable to the acoustic difference between a stimulus and the prototype. For the analyses and the interpretation of the experimental results the Signal Detection Theory (SDT) and the Exemplar Theory are used. Signal Detection Theory postulates that despite similar auditory abilities subjects may differ in their perceptual results because of their individual response criterion. Exemplar Theory proposes that listeners store their perceived instances of speech events in exemplar clouds located in their perceptual space, and that these instances are stored with much phonetic detail. During speech production, the speaker uses these clouds of similar exemplars to produce an instance of a speech event. Thus, speech perception and production are inseparably connected. The more exemplars are stored the more stable a speech category will get. Only stable categories can develop a category center and a Perceptual Magnet Effect. In various studies reaction times were found to be a reliable indicator for the simplicity of a perceptual decision. Thus, in the experiment presented in this thesis reaction times were measured for each individual decision. The results support the already known correlation, i.e. the more simple a perceptual decision is the lower the reaction time will be. To summarize, the results discussed in this thesis support the existence of prosodic categories in general, and especially those of the high and the low boundary tone in German. These two prosodic categories are used to differentiate between the sentence modes statement versus question, but only in case of syntactically ambiguous phrases. Furthermore, the results support the use on Exemplar Theory for speech data. The category of the low boundary tone seems to contain much more exemplars than the category of the high boundary tone as the latter category is less often produced and thus less often perceived than the first one. This results in a clear Perceptual Magnet Effect for the L% category as there enough exemplar are stored to support the development of a category center, and only in the center of a category the PME can occur. For most listeners the H% category contains only a few exemplars which in turn inhibits the development of a Perceptual Magnet Effect there. The logged reaction times support the perceptual findings and reveal the hypothesis that reaction times correlate with the simplicity of a perceptual decision.Item Open Access Event knowledge and models of logical metonymy interpretation(2014) Zarcone, Alessandra; Padó, Sebastian (Prof. Dr.)During language understanding, people do not only rely on what they read or hear, but they also exploit implicit information. For example, when they process the expression "begin the book", they understand it involves an event which is not explicitly mentioned (e.g. "begin reading the book). This thesis looks at these constructions, known as logical metonymies, which combine an event-selecting verb and entity-denoting object and involve covert events. Logical metonymies are an interesting challenge for theories of lexical semantics: they need to be reconciled with compositionality, they require the integration of context (writers typically write books, students typically read them), and they lie at the interface between lexicon and world knowledge (is the information that books are read stored in our mental lexicon or in our world knowledge?). I critically analyze previous hypotheses on logical metonymy with regard to the answer they provide to two core problems: the source problem (what events are retrieved? what type of event knowledge is assumed?) and the trigger problem (why do some constructions trigger a metonymic interpretation and others do not?). Lexicalist approaches claim that the metonymy arises from a type clash between the event-selecting verb and an entity-denoting object, and posit complex lexical items, encoding event information about artifacts (e.g. book: read), to explain the recovery of covert events. Pragmatic-based approaches argue against the idea that lexical items have an internal structure, suggesting that covert events arise from the underspecification of a logical metonymy and are inferred via non-lexical knowledge. I look with particular attention at the role of event knowledge, which lexicalist approaches place in our mental lexicon, while pragmatic-based approaches place it in our world knowledge. I propose a third hypothesis, based on thematic fit and generalized event knowledge of typical events and their participants, which have been shown to guide efficient incremental processing: I argue that contextual elements cue generalized event knowledge, which plays a key role in determining the covert event for a logical metonymy. I explore this hypothesis from an interdisciplinary perspective, employing both psycholinguistic experiments and computational models, in order to seek converging evidence and confront it with the theoretical investigation. The results from the psycholinguistic experiments and from the computational (distributional) models support the hypothesis that covert event retrieval is guided by generalized event knowledge. I also employ the computational models to analyze previous experimental results and to explore the hypothesis that thematic fit, informed by generalized event knowledge, is ultimately responsible for the trigger of the logical metonymy. I then report on more psycholinguistic evidence showing that a notion of type is indeed necessary to account for differences between metonymic and non-metonymic constructions, and that both type and thematic fit play a role in logical metonymy interpretation. Lastly, I argue for a context-sensitive model of logical metonymy interpretation that exploits an information-rich lexicon, but needs to rethink the notion of type and reconcile it with the notion of thematic fit.Item Open Access Where are emotions in text? A human-based and computational investigation of emotion recognition and generation(2023) Troiano, Enrica; Klinger, Roman (Prof. Dr.)Item Open Access Fehlerbehandlung in Mensch-Maschine-Dialogen(2007) Gieselmann, Petra; Rohrer, Christian (Prof.)Seit es Computer gibt, existiert auch der Wunsch des Menschen, mit ihnen reden zu können wie mit einem anderen Menschen. Eines der berühmtesten Beispiele dafür ist sicherlich Eliza, ein Computerprogramm, das einen Psychologen simuliert, mit dem der Benutzer ein Therapiegespräch führen kann. In vielen Science-Fiction-Filmen finden sich auch immer wieder Beispiele für solche sprechenden Maschinen, wie beispielsweise HAL in 2001: Odysee im Weltraum'' oder auch der Computer auf dem Raumschiff Enterprise''. So reichen erste Dialogsysteme bereits zurück bis in die Anfänge der künstlichen Intelligenz in den fünfziger Jahren. Dennoch hatten diese Dialogsysteme bis vor wenigen Jahren noch mit so vielen Problemen zu kämpfen, dass sie kaum für einen praktischen Einsatz geeignet waren. Erst in letzter Zeit ist es durch die stetigen Verbesserungen im Bereich von Spracherkennung und Sprachverstehen und das Aufkommen von immer schnelleren und mächtigeren Rechnern möglich geworden, solche Systeme für den realen Einsatz zu bauen. Nach wie vor gibt es aber noch eine ganze Reihe ungelöster Probleme, die zum einen auf die Komplexität natürlicher Sprache und zum anderen auf den immensen Fundus an vernetztem Weltwissen und Kontextbeziehungen, über den Menschen verfügen, zurückzuführen sind. Eine der bislang größten Herausforderungen liegt darin, ein solches Dialogsystem auch für den realen Einsatz unter Alltagsbedingungen zu entwerfen. Bisher fehlt den Systemen dafür noch die nötige Fehlerrobustheit, um in Situationen, in denen das System etwas falsch verstanden hat und es zu Problemen kommt, angemessen reagieren zu können. In dieser Arbeit geht es genau um solche Fehler im Dialog, wie sie vermieden und während des laufenden Dialogs wieder behoben werden können, wenn sie nicht vorher zu vermeiden waren. Der Gegenstand dieser Arbeit ist eine datengetriebene Analyse der Fehler, die in der Mensch-Roboter-Kommunikation auftreten mit dem Ziel, diese möglichst im Vorfeld zu vermeiden. Es wird eine Fehlerklassifikation aufgestellt und es werden Methoden für die Vermeidung der verschiedenen Fehlerklassen entwickelt und evaluiert. Darüberhinaus werden auch generische Methoden zur Fehlerbehebung für die Fälle implementiert, die nicht vorher vermieden werden konnten, ebenfalls mit Hilfe datengetriebener Analysen. Damit soll es ermöglicht werden, Dialogsysteme über die Laborumgebung hinaus in realen Situationen einsetzen zu können. Dies wird am Beispiel eines Haushaltsroboters diskutiert und evaluiert. Diese Ausarbeitung gliedert sich in vier Teile: Der erste Teil beschäftigt sich mit dem Stand der Forschung in den Bereichen, die hier eine Rolle spielen. Dazu werden verschiedene Ansätze für Mensch-Maschine-Dialogsysteme beleuchtet. Im Anschluss wird die menschliche Informationsverarbeitung im Dialogbereich erläutert. Dabei geht es auch um Fehlerdialoge in zwischenmenschlichen Dialogen, die hier als Vorbild für Mensch-Roboter-Dialoge dienen. Der zweite Teil beschäftigt sich mit den durchgeführten Benutzertests und Datensammlungen und der Klassifikation von Fehlern im Dialog, die die Grundlage für die folgenden Arbeiten zur Fehlervermeidung und -behebung bilden. Zunächst erfolgt eine detaillierte Analyse von Fehlern, die bei der Mensch-Roboter-Interaktion auftreten können. Dazu werden verschiedene aufeinander aufbauende Benutzerstudien und Datensammlungen, bei denen der Roboter dem Menschen im Haushalt zur Hand geht und einfache Tätigkeiten verrichtet, durchgeführt, um eine große Menge an möglichst realistischen Daten gewinnen zu können, die nicht nur unter Laborbedingungen entstanden sind. Im dritten Teil werden verschiedene Methoden zur Fehlervermeidung und -behebung vorgestellt. Zur Fehlervermeidung werden zusätzliche Wissensquellen in den Dialogmanager integriert. Außerdem werden Mechanismen zur Anaphernresolution, Kontextmodellierung, Auflösung von Ellipsen, multimodalen Fusion und zum Umgang mit komplexen, zusammengesetzten Äußerungen entwickelt und evaluiert. Zur Fehlerbehebung werden verschiedene Strategien für effektive Klärungsfragen untersucht. Metakommunikation, wie sie in den durchgeführten Benutzertests vorkommt, wird analysiert, um eine effektivere Kommunikation gewährleisten zu können. Außerdem wird ein Mechanismus entwickelt, der es dem Roboter erlaubt, problematische Situationen zu erkennen und diese selbst durch Metakommunikation aufzulösen. Im vierten Teil werden die entwickelten Methoden anhand eines abschließenden Benutzertests evaluiert. Dabei geht es darum, das System mit allen entwickelten Mechanismen zur Fehlerbehandlung zu testen und es mit dem Basissystem zu vergleichen. Das besondere Augenmerk liegt hier auf der Übertragbarkeit der entwickelten Mechanismen auf andere Domänen und Systeme. Danach folgt das Fazit der gesamten Arbeit und eine Diskussion der zukünftigen Arbeiten im Hinblick auf mögliche Erweiterungen dieses Systems.