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Intro; Preface; Organization; Abstracts of Invited Talks; Mitigating Gender Bias in Morphologically Rich Languages; Adversarial Attacks on ML Systems; Multiword Expressions and Idiomaticity: How Much of the Sailing Has Been Plain?; Contents; Keynote Talks; Speech Processing and Prosody; 1 Introduction; 2 Computing Prosodic Features; 2.1 Phone Duration; 2.2 Fundamental Frequency; 2.3 Phone Energy; 3 Reliabity of Prosodic Features; 3.1 Speech-Text Alignments; 3.2 Phone Duration; 3.3 Fundamental Frequency; 4 Prosodic Features in Automatic Speech Processing

4.1 Computer Assisted Language Learning4.2 Structuring Speech Utterances; 4.3 Sentence Modality; 4.4 Prosodic Correlates of Discourse Particles; 4.5 Expressive Speech; 5 Conclusion; References; Text; Using a Database of Multiword Expressions in Dependency Parsing; 1 Introduction; 2 ``A Pain in the Neck for NLP''; 3 Syntactic Representation of Multiword Expressions; 4 The LEMUR Database; 4.1 The Structure of the Database; 4.2 Idiomaticity; 4.3 Variability; 4.4 Syntactic Structure; 5 Identification of MWEs in Texts; 5.1 Annotation of MWEs in Corpora

6 Parsing of Text Containing MWEs Using Data from the LEMUR Database6.1 Identification of Parsing Errors of MWEs; 6.2 Correction of Parsing Errors of MWEs; 7 Conclusion; References; Explicit Discourse Argument Extraction for German; 1 Introduction; 2 Related Work; 3 Data; 4 Method; 4.1 arg2 Extraction; 4.2 arg1 Extraction; 5 Results and Evaluation; 5.1 arg2 Extraction; 5.2 arg1 Extraction; 6 Conclusion and Outlook; References; Consonance as a Stylistic Feature for Authorship Attribution of Historical Texts; 1 Introduction; 2 Consonance; 2.1 Definition; 2.2 Extracting Consonance from Text

3 Consonance Experiments3.1 The 18th-Century Corpus; 3.2 The Victorian Corpus; 3.3 Additional Observations; 4 Conclusion and Future Work; References; Bidirectional LSTM Tagger for Latvian Grammatical Error Detection; 1 Introduction; 2 Error Types in English and in Latvian Corpora; 3 Error-Annotated Data and Artificial Error Generation; 4 Neural Network Solutions Used for Grammaticality Testing; 5 Experiments; 5.1 Preparation of Data; 5.2 Model Training; 6 Results and Discussion; 7 Conclusion and Future Work; References; Methods for Assessing Theme Adherence in Student Thesis; 1 Introduction

2 Related Works3 Task, Data and Preprocessing; 4 Preprocessing of Thesis Text; 5 Methods of Assessing Theme Adherence; 5.1 Baselines; 5.2 Probabilistic Topic Modeling; 5.3 Features of Theme Adherence Assessment; 6 Evaluation and Results; 6.1 Configurations Evaluation; 6.2 Hyperparameter Analysis; 7 Conclusion; References; Natural Language Analysis to Detect Parkinson's Disease; 1 Introduction; 2 Data; 3 Methods; 3.1 Train, Development, and Test Data Distribution; 3.2 Pre-processing; 3.3 Feature Extraction; 3.4 Classification; 4 Results and Discussion; 5 Conclusion; References

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