Marc Schulder
Marc Schulder
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Enhancing a Lexicon of Polarity Shifters through the Supervised Classification of Shifting Directions
Abstract The sentiment polarity of an expression (whether it is perceived as positive, negative or neutral) can be influenced by a number of phenomena, foremost among them negation. Apart from closed-class negation words like no, not or without, negation can also be caused by so-called polarity shifters.
Marc Schulder
,
Michael Wiegand
,
Josef Ruppenhofer
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Automatically Creating a Lexicon of Verbal Polarity Shifters: Mono- and Cross-lingual Methods for German
Abstract In this paper we use methods for creating a large lexicon of verbal polarity shifters and apply them to German. Polarity shifters are content words that can move the polarity of a phrase towards its opposite, such as the verb “abandon” in “abandon all hope”.
Marc Schulder
,
Michael Wiegand
,
Josef Ruppenhofer
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Poster
DOI
Introducing a Lexicon of Verbal Polarity Shifters for English
Abstract The sentiment polarity of a phrase does not only depend on the polarities of its words, but also on how these are affected by their context. Negation words (e.g. not, no, never) can change the polarity of a phrase.
Marc Schulder
,
Michael Wiegand
,
Josef Ruppenhofer
,
Stephanie Köser
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Slides
DOI
Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features
Abstract We present a major step towards the creation of the first high-coverage lexicon of polarity shifters. In this work, we bootstrap a lexicon of verbs by exploiting various linguistic features.
Marc Schulder
,
Michael Wiegand
,
Josef Ruppenhofer
,
Benjamin Roth
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Slides
DOI
Quantifying the Benefits of Speech Recognition for an Air Traffic Management Application
Abstract The project AcListant® (Active Listening Assistant), which uses automatic speech recognition to recognize the commands in air traffic controller to pilot communication, has achieved command recognition rates above 95%. These high rates were obtained with an Assistance-Based Speech Recognition (ABSR).
Hartmut Helmke
,
Youssef Oualil
,
Marc Schulder
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Project
Separating Actor-View from Speaker-View Opinion Expressions using Linguistic Features
Abstract We examine different features and classifiers for the categorization of opinion words into actor and speaker view. To our knowledge, this is the first comprehensive work to address sentiment views on the word level taking into consideration opinion verbs, nouns and adjectives.
Michael Wiegand
,
Marc Schulder
,
Josef Ruppenhofer
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Project
DOI
Opinion Holder and Target Extraction for Verb-based Opinion Predicates – The Problem is Not Solved
Abstract We offer a critical review of the current state of opinion role extraction involving opinion verbs. We argue that neither the currently available lexical resources nor the manually annotated text corpora are sufficient to appropriately study this task.
Michael Wiegand
,
Marc Schulder
,
Josef Ruppenhofer
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Project
DOI
Real-Time Integration of Dynamic Context Information for Improving Automatic Speech Recognition
Abstract The use of prior situational/contextual knowledge about a given task can significantly improve Automatic Speech Recognition (ASR) performance. This is typically done through adaptation of acoustic or language models if data is available, or using knowledge-based rescoring.
Youssef Oualil
,
Marc Schulder
,
Hartmut Helmke
,
Anna Schmidt
,
Dietrich Klakow
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Project
Assistant-Based Speech Recognition for ATM Applications
Abstract Situation awareness of today’s automation relies so far on sensor information, data bases and the information delivered by the operator using an appropriate user interface. Listening to the conversation of people is not addressed until today, but an asset in many working situations of teams.
Hartmut Helmke
,
Jürgen Rataj
,
Thorsten Mühlhausen
,
Oliver Ohneiser
,
Heiko Ehr
,
Matthias Kleinert
,
Youssef Oualil
,
Marc Schulder
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Project
Slides
Context-based recognition network adaptation for improving on-line ASR in Air Traffic Control
Abstract This paper presents an approach for incorporating situational context information into an on-line Automatic Speech Recognition (ASR) component of an Air Traffic Control (ATC) assistance system to improve recognition performance.
Anna Schmidt
,
Youssef Oualil
,
Oliver Ohneiser
,
Matthias Kleinert
,
Marc Schulder
,
Arif Khan
,
Hartmut Helmke
,
Dietrich Klakow
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Project
DOI
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