Publications

• https://www.cambridgescholars.com/product/978-1-5275-7432-8

@inbook{Menzel2021_eponyms,
title = {Scientific Eponyms throughout the History of English Scholarly Journal Articles},
author = {Katrin Menzel},
editor = {Hans Van de Velde and Fredric T. Dolezal},
url = {https://www.cambridgescholars.com/product/978-1-5275-7432-8},
year = {2021},
date = {2021-11-08},
booktitle = {Broadening Perspectives in the History of Dictionaries and Word Studies},
isbn = {1-5275-7432-6},
pages = {159-193},
publisher = {Cambridge Scholars Publishing},
address = {Newcastle upon Tyne},
pubstate = {published},
type = {inbook}
}

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Recently, Ankener et al. (Frontiers in Psychology, 9, 2387, 2018) presented a visual world study which combined both attention and pupillary measures to demonstrate that anticipating a target results in lower effort to integrate that target (noun). However, they found no indication that the anticipatory processes themselves, i.e., the reduction of uncertainty about upcoming referents, results in processing effort (cf. Linzen and Jaeger, Cognitive Science, 40(6), 1382–1411, 2016). In contrast, Maess et al. (Frontiers in Human Neuroscience, 10, 1–11, 2016) found that more constraining verbs elicited a higher N400 amplitude than unconstraining verbs. The aim of the present study was therefore twofold: Firstly, we examined whether the graded ICA effect, which was previously found on the noun as a result of a likelihood manipulation, replicates in ERP measures. Secondly, we set out to investigate whether the processes leading to the generation of expectations (derived during verb and scene processing) induce an N400 modulation. Our results confirm that visual context is combined with the verb’s meaning to establish expectations about upcoming nouns and that these expectations affect the retrieval of the upcoming noun (modulated N400 on the noun). Importantly, however, we find no evidence for different costs in generating more or less specific expectations for upcoming nouns. Thus, the benefits of generating expectations are not associated with any costs in situated language comprehension.

• https://link.springer.com/article/10.3758/s13423-020-01827-3
• https://doi.org/10.3758/s13423-020-01827-3

@article{staudte2021,
title = {Graded expectations in visually situated comprehension: Costs and benefits as indexed by the N400},
author = {Maria Staudte and Christine Ankener and Heiner Drenhaus and Matthew W. Crocker},
url = {https://link.springer.com/article/10.3758/s13423-020-01827-3},
doi = {https://doi.org/10.3758/s13423-020-01827-3},
year = {2021},
date = {2021},
journal = {Psychonomic Bulletin & Review},
pages = {624-631},
publisher = {Springer},
volume = {28},
number = {2},
abstract = {Recently, Ankener et al. (Frontiers in Psychology, 9, 2387, 2018) presented a visual world study which combined both attention and pupillary measures to demonstrate that anticipating a target results in lower effort to integrate that target (noun). However, they found no indication that the anticipatory processes themselves, i.e., the reduction of uncertainty about upcoming referents, results in processing effort (cf. Linzen and Jaeger, Cognitive Science, 40(6), 1382–1411, 2016). In contrast, Maess et al. (Frontiers in Human Neuroscience, 10, 1–11, 2016) found that more constraining verbs elicited a higher N400 amplitude than unconstraining verbs. The aim of the present study was therefore twofold: Firstly, we examined whether the graded ICA effect, which was previously found on the noun as a result of a likelihood manipulation, replicates in ERP measures. Secondly, we set out to investigate whether the processes leading to the generation of expectations (derived during verb and scene processing) induce an N400 modulation. Our results confirm that visual context is combined with the verb’s meaning to establish expectations about upcoming nouns and that these expectations affect the retrieval of the upcoming noun (modulated N400 on the noun). Importantly, however, we find no evidence for different costs in generating more or less specific expectations for upcoming nouns. Thus, the benefits of generating expectations are not associated with any costs in situated language comprehension.},
pubstate = {published},
type = {article}
}

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@miscellaneous{HoeltjeMecklinger2021,
title = {The Secret Life of (Dis-)Confirmed Predictions: Effects of Sentence Constraint and Word Expectedness on Episodic Memory Formation, and how they are Reflected in Event-Related Potentials},
author = {Gerrit H{\"o}ltje and Axel Mecklinger},
year = {2021},
date = {2021},
booktitle = {CNS 2020 Virtual meeting, Abstract Book},
pubstate = {published},
type = {miscellaneous}
}

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Endeavors to computationally model language variation and change are ever increasing. While analyses of recent diachronic trends are frequently conducted, long-term trends accounting for sociolinguistic variation are less well-studied. Our work sheds light on the temporal dynamics of language use of British 18th century women as a group in transition across two situational contexts. Our findings reveal that in formal contexts women adapt to register conventions, while in informal contexts they act as innovators of change in language use influencing others. While adopted from other disciplines, our methods inform (historical) sociolinguistic work in novel ways. These methods include diachronic periodization by Kullback-Leibler divergence to determine periods of change and relevant features of variation, and event cascades as influencer models.

• frai-04-609970     (3.66MB)
• https://www.frontiersin.org/article/10.3389/frai.2021.609970
• https://doi.org/10.3389/frai.2021.609970

@article{Degaetano-Ortlieb2021,
title = {Registerial Adaptation vs. Innovation Across Situational Contexts: 18th Century Women in Transition},
author = {Stefania Degaetano-Ortlieb and Tanja S{\"a}ily and Yuri Bizzoni},
url = {https://www.frontiersin.org/article/10.3389/frai.2021.609970},
doi = {https://doi.org/10.3389/frai.2021.609970},
year = {2021},
date = {2021},
journal = {Frontiers in Artificial Intelligence, section Language and Computation},
volume = {4},
abstract = {Endeavors to computationally model language variation and change are ever increasing. While analyses of recent diachronic trends are frequently conducted, long-term trends accounting for sociolinguistic variation are less well-studied. Our work sheds light on the temporal dynamics of language use of British 18th century women as a group in transition across two situational contexts. Our findings reveal that in formal contexts women adapt to register conventions, while in informal contexts they act as innovators of change in language use influencing others. While adopted from other disciplines, our methods inform (historical) sociolinguistic work in novel ways. These methods include diachronic periodization by Kullback-Leibler divergence to determine periods of change and relevant features of variation, and event cascades as influencer models.},
pubstate = {published},
type = {article}
}

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The present paper deals with a computational analysis of translationese in professional and student English-to-German translations belonging to different registers. Building upon an information-theoretical approach, we test translation conformity to source and target language in terms of a neural language model’s perplexity over Part of Speech (PoS) sequences. Our primary focus is on register diversification vs. convergence, reflected in the use of constructions eliciting a higher vs. lower perplexity score. Our results show that, against our expectations, professional translations elicit higher perplexity scores from a target language model than students’ translations. An analysis of the distribution of PoS patterns across registers shows that this apparent paradox is the effect of higher stylistic diversification and register sensitivity in professional translations. Our results contribute to the understanding of human translationese and shed light on the variation in texts generated by different translators, which is valuable for translation studies, multilingual language processing, and machine translation.

• https://aclanthology.org/2021.nodalida-main.6

@inproceedings{Bizzoni2021,
title = {Measuring Translationese across Levels of Expertise: Are Professionals more Surprising than Students?},
author = {Yuri Bizzoni and Ekaterina Lapshinova-Koltunski},
url = {https://aclanthology.org/2021.nodalida-main.6},
year = {2021},
date = {2021},
booktitle = {Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)},
pages = {53-63},
publisher = {Link{\"o}ping University Electronic Press, Sweden},
abstract = {The present paper deals with a computational analysis of translationese in professional and student English-to-German translations belonging to different registers. Building upon an information-theoretical approach, we test translation conformity to source and target language in terms of a neural language model’s perplexity over Part of Speech (PoS) sequences. Our primary focus is on register diversification vs. convergence, reflected in the use of constructions eliciting a higher vs. lower perplexity score. Our results show that, against our expectations, professional translations elicit higher perplexity scores from a target language model than students’ translations. An analysis of the distribution of PoS patterns across registers shows that this apparent paradox is the effect of higher stylistic diversification and register sensitivity in professional translations. Our results contribute to the understanding of human translationese and shed light on the variation in texts generated by different translators, which is valuable for translation studies, multilingual language processing, and machine translation.},
pubstate = {published},
type = {inproceedings}
}

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Expectation-based theories of language processing, such as Surprisal theory, are supported by evidence of anticipation effects in both behavioural and neurophysiological measures. Online measures of language processing, however, are known to be influenced by factors such as lexical association that are distinct from—but often confounded with—expectancy. An open question therefore is whether a specific locus of expectancy related effects can be established in neural and behavioral processing correlates. We address this question in an event-related potential experiment and a self-paced reading experiment that independently cross expectancy and lexical association in a context manipulation design. We find that event-related potentials reveal that the N400 is sensitive to both expectancy and lexical association, while the P600 is modulated only by expectancy. Reading times, in turn, reveal effects of both association and expectancy in the first spillover region, followed by effects of expectancy alone in the second spillover region. These findings are consistent with the Retrieval-Integration account of language comprehension, according to which lexical retrieval (N400) is facilitated for words that are both expected and associated, whereas integration difficulty (P600) will be greater for unexpected words alone. Further, an exploratory analysis suggests that the P600 is not merely sensitive to expectancy violations, but rather, that there is a continuous relation. Taken together, these results suggest that the P600, like reading times, may reflect a meaning-centric notion of Surprisal in language comprehension.

• https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0257430
• https://doi.org/10.1371/journal.pone.0257430

@article{aurnhammer2021retrieval,
title = {Retrieval (N400) and Integration (P600) in Expectation-based Comprehension},
author = {Christoph Aurnhammer and Francesca Delogu and Miriam Schulz and Harm Brouwer and Matthew W. Crocker},
url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0257430},
doi = {https://doi.org/10.1371/journal.pone.0257430},
year = {2021},
date = {2021-09-28},
journal = {PLoS ONE},
pages = {e0257430},
volume = {16},
number = {9},
abstract = {Expectation-based theories of language processing, such as Surprisal theory, are supported by evidence of anticipation effects in both behavioural and neurophysiological measures. Online measures of language processing, however, are known to be influenced by factors such as lexical association that are distinct from—but often confounded with—expectancy. An open question therefore is whether a specific locus of expectancy related effects can be established in neural and behavioral processing correlates. We address this question in an event-related potential experiment and a self-paced reading experiment that independently cross expectancy and lexical association in a context manipulation design. We find that event-related potentials reveal that the N400 is sensitive to both expectancy and lexical association, while the P600 is modulated only by expectancy. Reading times, in turn, reveal effects of both association and expectancy in the first spillover region, followed by effects of expectancy alone in the second spillover region. These findings are consistent with the Retrieval-Integration account of language comprehension, according to which lexical retrieval (N400) is facilitated for words that are both expected and associated, whereas integration difficulty (P600) will be greater for unexpected words alone. Further, an exploratory analysis suggests that the P600 is not merely sensitive to expectancy violations, but rather, that there is a continuous relation. Taken together, these results suggest that the P600, like reading times, may reflect a meaning-centric notion of Surprisal in language comprehension.},
pubstate = {published},
type = {article}
}

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DiscAlign for Penn and RST Discourse Treebanks was developed by Saarland University. It consists of alignment information for the discourse annotations contained in Penn Discourse Treebank Version 2.0 (LDC2008T05) (PDTB 2.0) and RST Discourse Treebank (LDC2002T07) (RST-DT). PDTB 2.0 and RST-DT annotations overlap for 385 newspaper articles in sections 6, 11, 13, 19 and 23 of the Wall Street Journal corpus contained in Treebank-2 (LDC95T7). DiscAlign for Penn and RST Discourse Treebanks contains approximately 6,700 alignments between PDTB 2.0 and RST-DT relations.

• https://catalog.ldc.upenn.edu/LDC2021T16
• https://doi.org/10.35111/cf0q-c454

@miscellaneous{Demberg_etal_DiscAlign,
title = {DiscAlign for Penn and RST Discourse Treebanks},
author = {Vera Demberg and Fatemeh Torabi Asr and Merel Scholman},
url = {https://catalog.ldc.upenn.edu/LDC2021T16},
doi = {https://doi.org/10.35111/cf0q-c454},
year = {2021},
date = {2021},
isbn = {1-58563-975-3},
publisher = {Linguistic Data Consortium},
address = {Philadelphia},
abstract = {DiscAlign for Penn and RST Discourse Treebanks was developed by Saarland University. It consists of alignment information for the discourse annotations contained in Penn Discourse Treebank Version 2.0 (LDC2008T05) (PDTB 2.0) and RST Discourse Treebank (LDC2002T07) (RST-DT). PDTB 2.0 and RST-DT annotations overlap for 385 newspaper articles in sections 6, 11, 13, 19 and 23 of the Wall Street Journal corpus contained in Treebank-2 (LDC95T7). DiscAlign for Penn and RST Discourse Treebanks contains approximately 6,700 alignments between PDTB 2.0 and RST-DT relations.},
pubstate = {published},
type = {miscellaneous}
}

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In this paper, we investigate grammatical complexity as a register feature of scientific English and German. Specifically, we carry out a diachronic comparison between general and scientific discourse in the two languages from the 17th to the 19th century, using relativizers as proxies for grammatical complexity. We ground our study in register theory (Halliday and Hasan, 1985), assuming that language use reflects contextual factors, which contribute to the formation of registers (Quirk et al., 1985; Biber et al., 1999; Teich et al., 2016). Our findings show a clear tendency towards grammatical simplification in scientific discourse in both languages with English spearheading the trend early on and German following later.

• https://doi.org/10.15845/bells.v11i1.3440
• https://doi.org/10.15845/bells.v11i1.3440

@article{Krielke2021relativizers,
title = {Relativizers as markers of grammatical complexity: A diachronic, cross-register study of English and German},
author = {Marie-Pauline Krielke},
url = {https://doi.org/10.15845/bells.v11i1.3440},
doi = {https://doi.org/10.15845/bells.v11i1.3440},
year = {2021},
date = {2021-09-15},
journal = {Bergen Language and Linguistics Studies},
pages = {91-120},
volume = {11},
number = {1},
abstract = {In this paper, we investigate grammatical complexity as a register feature of scientific English and German. Specifically, we carry out a diachronic comparison between general and scientific discourse in the two languages from the 17th to the 19th century, using relativizers as proxies for grammatical complexity. We ground our study in register theory (Halliday and Hasan, 1985), assuming that language use reflects contextual factors, which contribute to the formation of registers (Quirk et al., 1985; Biber et al., 1999; Teich et al., 2016). Our findings show a clear tendency towards grammatical simplification in scientific discourse in both languages with English spearheading the trend early on and German following later.},
pubstate = {published},
type = {article}
}

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Previous studies have shown that at moderate levels of spectral degradation, semantic predictability facilitates language comprehension. It is argued that when speech is degraded, listeners have narrowed expectations about the sentence endings; i.e., semantic prediction may be limited to only most highly predictable sentence completions. The main objectives of this study were to (i) examine whether listeners form narrowed expectations or whether they form predictions across a wide range of probable sentence endings, (ii) assess whether the facilitatory effect of semantic predictability is modulated by perceptual adaptation to degraded speech, and (iii) use and establish a sensitive metric for the measurement of language comprehension. For this, we created 360 German Subject-Verb-Object sentences that varied in semantic predictability of a sentence-final target word in a graded manner (high, medium, and low) and levels of spectral degradation (1, 4, 6, and 8 channels noise-vocoding). These sentences were presented auditorily to two groups: One group (n =48) performed a listening task in an unpredictable channel context in which the degraded speech levels were randomized, while the other group (n =50) performed the task in a predictable channel context in which the degraded speech levels were blocked. The results showed that at 4 channels noise-vocoding, response accuracy was higher in high-predictability sentences than in the medium-predictability sentences, which in turn was higher than in the low-predictability sentences. This suggests that, in contrast to the narrowed expectations view, comprehension of moderately degraded speech, ranging from low- to high- including medium-predictability sentences, is facilitated in a graded manner; listeners probabilistically preactivate upcoming words from a wide range of semantic space, not limiting only to highly probable sentence endings. Additionally, in both channel contexts, we did not observe learning effects; i.e., response accuracy did not increase over the course of experiment, and response accuracy was higher in the predictable than in the unpredictable channel context. We speculate from these observations that when there is no trial-by-trial variation of the levels of speech degradation, listeners adapt to speech quality at a long timescale; however, when there is a trial-by-trial variation of the high-level semantic feature (e.g., sentence predictability), listeners do not adapt to low-level perceptual property (e.g., speech quality) at a short timescale.

• https://www.frontiersin.org/articles/10.3389/fpsyg.2021.714485/full
• https://doi.org/10.3389/fpsyg.2021.714485

@article{bhandari2021semantic,
title = {Semantic Predictability Facilitates Comprehension of Degraded Speech in a Graded Manner},
author = {Pratik Bhandari and Vera Demberg and Jutta Kray},
url = {https://www.frontiersin.org/articles/10.3389/fpsyg.2021.714485/full},
doi = {https://doi.org/10.3389/fpsyg.2021.714485},
year = {2021},
date = {2021-09-09},
journal = {Frontiers in Psychology},
pages = {3769},
publisher = {Frontiers},
abstract = {Previous studies have shown that at moderate levels of spectral degradation, semantic predictability facilitates language comprehension. It is argued that when speech is degraded, listeners have narrowed expectations about the sentence endings; i.e., semantic prediction may be limited to only most highly predictable sentence completions. The main objectives of this study were to (i) examine whether listeners form narrowed expectations or whether they form predictions across a wide range of probable sentence endings, (ii) assess whether the facilitatory effect of semantic predictability is modulated by perceptual adaptation to degraded speech, and (iii) use and establish a sensitive metric for the measurement of language comprehension. For this, we created 360 German Subject-Verb-Object sentences that varied in semantic predictability of a sentence-final target word in a graded manner (high, medium, and low) and levels of spectral degradation (1, 4, 6, and 8 channels noise-vocoding). These sentences were presented auditorily to two groups: One group (n =48) performed a listening task in an unpredictable channel context in which the degraded speech levels were randomized, while the other group (n =50) performed the task in a predictable channel context in which the degraded speech levels were blocked. The results showed that at 4 channels noise-vocoding, response accuracy was higher in high-predictability sentences than in the medium-predictability sentences, which in turn was higher than in the low-predictability sentences. This suggests that, in contrast to the narrowed expectations view, comprehension of moderately degraded speech, ranging from low- to high- including medium-predictability sentences, is facilitated in a graded manner; listeners probabilistically preactivate upcoming words from a wide range of semantic space, not limiting only to highly probable sentence endings. Additionally, in both channel contexts, we did not observe learning effects; i.e., response accuracy did not increase over the course of experiment, and response accuracy was higher in the predictable than in the unpredictable channel context. We speculate from these observations that when there is no trial-by-trial variation of the levels of speech degradation, listeners adapt to speech quality at a long timescale; however, when there is a trial-by-trial variation of the high-level semantic feature (e.g., sentence predictability), listeners do not adapt to low-level perceptual property (e.g., speech quality) at a short timescale.},
pubstate = {published},
type = {article}
}

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Due to a lack of annotated data, theories of historical syntax are often based on very small, manually compiled data sets. To enable the empirical evaluation of existing hypotheses, the present study explores the automatic recognition of phrases in historical German. Using modern and historical treebanks, training data for a neural sequence labeling tool and a probabilistic parser is created, and both methods are compared on a variety of data sets. The evaluation shows that the unlexicalized parser outperforms the sequence labeling approach, achieving F1-scores of 87%–91% on modern German and between 73% and 85% on different historical corpora. An error analysis indicates that accuracy decreases especially for longer phrases, but most of the errors concern incorrect phrase boundaries, suggesting further potential for improvement.

• 2021.konvens-1.11     (1.27MB)
• https://aclanthology.org/2021.konvens-1.11

@inproceedings{ortmann-2021b,
title = {Automatic Phrase Recognition in Historical German},
author = {Katrin Ortmann},
url = {https://aclanthology.org/2021.konvens-1.11},
year = {2021},
date = {2021-09-06},
booktitle = {Proceedings of the 17th Conference on Natural Language Processing (KONVENS 2021)},
pages = {127–136},
publisher = {KONVENS 2021 Organizers},
address = {D{\"u}sseldorf, Germany},
abstract = {Due to a lack of annotated data, theories of historical syntax are often based on very small, manually compiled data sets. To enable the empirical evaluation of existing hypotheses, the present study explores the automatic recognition of phrases in historical German. Using modern and historical treebanks, training data for a neural sequence labeling tool and a probabilistic parser is created, and both methods are compared on a variety of data sets. The evaluation shows that the unlexicalized parser outperforms the sequence labeling approach, achieving F1-scores of 87%–91% on modern German and between 73% and 85% on different historical corpora. An error analysis indicates that accuracy decreases especially for longer phrases, but most of the errors concern incorrect phrase boundaries, suggesting further potential for improvement.},
pubstate = {published},
type = {inproceedings}
}

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We present an extended version of a tool developed for calculating linguistic distances and asymmetries in auditory perception of closely related languages. Along with evaluating the metrics available in the initial version of the tool, we introduce word adaptation entropy as an additional metric of linguistic asymmetry. Potential predictors of speech intelligibility are validated with human performance in spoken cognate recognition experiments for Bulgarian and Russian. Special attention is paid to the possibly different contributions of vowels and consonants in oral intercomprehension. Using incom.py 2.0 it is possible to calculate, visualize, and validate three measurement methods of linguistic distances and asymmetries as well as carrying out regression analyses in speech intelligibility between related languages.

• https://aclanthology.org/2021.ranlp-1.110/

@inproceedings{mosbach-etal-2021-incom,
title = {incom.py 2.0 - Calculating Linguistic Distances and Asymmetries in Auditory Perception of Closely Related Languages},
author = {Marius Mosbach and Irina Stenger and Tania Avgustinova and Bernd M{\"o}bius and Dietrich Klakow},
url = {https://aclanthology.org/2021.ranlp-1.110/},
year = {2021},
date = {2021-09-01},
booktitle = {Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)},
pages = {968-977},
publisher = {INCOMA Ltd.},
address = {Held Online},
abstract = {We present an extended version of a tool developed for calculating linguistic distances and asymmetries in auditory perception of closely related languages. Along with evaluating the metrics available in the initial version of the tool, we introduce word adaptation entropy as an additional metric of linguistic asymmetry. Potential predictors of speech intelligibility are validated with human performance in spoken cognate recognition experiments for Bulgarian and Russian. Special attention is paid to the possibly different contributions of vowels and consonants in oral intercomprehension. Using incom.py 2.0 it is possible to calculate, visualize, and validate three measurement methods of linguistic distances and asymmetries as well as carrying out regression analyses in speech intelligibility between related languages.},
pubstate = {published},
type = {inproceedings}
}

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Traditional hand-crafted linguistically-informed features have often been used for distinguishing between translated and original non-translated texts. By contrast, to date, neural architectures without manual feature engineering have been less explored for this task. In this work, we (i) compare the traditional feature-engineering-based approach to the feature-learning-based one and (ii) analyse the neural architectures in order to investigate how well the hand-crafted features explain the variance in the neural models’ predictions. We use pre-trained neural word embeddings, as well as several end-to-end neural architectures in both monolingual and multilingual settings and compare them to feature-engineering-based SVM classifiers. We show that (i) neural architectures outperform other approaches by more than 20 accuracy points, with the BERT-based model performing the best in both the monolingual and multilingual settings; (ii) while many individual hand-crafted translationese features correlate with neural model predictions, feature importance analysis shows that the most important features for neural and classical architectures differ; and (iii) our multilingual experiments provide empirical evidence for translationese universals across languages.

• 2021.emnlp-main.676     (0.41MB)
• https://aclanthology.org/2021.emnlp-main.676/
• https://doi.org/10.18653/v1/2021.emnlp-main.676

@inproceedings{pylypenko-etal-2021-comparing,
title = {Comparing Feature-Engineering and Feature-Learning Approaches for Multilingual Translationese Classification},
author = {Daria Pylypenko and Kwabena Amponsah-Kaakyire and Koel Dutta Chowdhury and Josef van Genabith and Cristina Espa{\~n}a-Bonet},
url = {https://aclanthology.org/2021.emnlp-main.676/},
doi = {https://doi.org/10.18653/v1/2021.emnlp-main.676},
year = {2021},
date = {2021},
booktitle = {Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing},
pages = {8596–8611},
publisher = {Association for Computational Linguistics},
address = {Online and Punta Cana, Dominican Republic},
abstract = {Traditional hand-crafted linguistically-informed features have often been used for distinguishing between translated and original non-translated texts. By contrast, to date, neural architectures without manual feature engineering have been less explored for this task. In this work, we (i) compare the traditional feature-engineering-based approach to the feature-learning-based one and (ii) analyse the neural architectures in order to investigate how well the hand-crafted features explain the variance in the neural models’ predictions. We use pre-trained neural word embeddings, as well as several end-to-end neural architectures in both monolingual and multilingual settings and compare them to feature-engineering-based SVM classifiers. We show that (i) neural architectures outperform other approaches by more than 20 accuracy points, with the BERT-based model performing the best in both the monolingual and multilingual settings; (ii) while many individual hand-crafted translationese features correlate with neural model predictions, feature importance analysis shows that the most important features for neural and classical architectures differ; and (iii) our multilingual experiments provide empirical evidence for translationese universals across languages.},
pubstate = {published},
type = {inproceedings}
}

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Previous research has used linguistic features to show that translations exhibit traces of source language interference and that phylogenetic trees between languages can be reconstructed from the results of translations into the same language. Recent research has shown that instances of translationese (source language interference) can even be detected in embedding spaces, comparing embeddings spaces of original language data with embedding spaces resulting from translations into the same language, using a simple Eigenvectorbased divergence from isomorphism measure. To date, it remains an open question whether alternative graph-isomorphism measures can produce better results. In this paper, we (i) explore Gromov-Hausdorff distance, (ii) present a novel spectral version of the Eigenvectorbased method, and (iii) evaluate all approaches against a broad linguistic typological database (URIEL). We show that language distances resulting from our spectral isomorphism approaches can reproduce genetic trees on a par with previous work without requiring any explicit linguistic information and that the results can be extended to non-Indo-European languages. Finally, we show that the methods are robust under a variety of modeling conditions.

• https://aclanthology.org/2021.ranlp-1.43/

@inproceedings{Chowdhury2021tracing,
title = {Tracing Source Language Interference in Translation with Graph-Isomorphism Measures},
author = {Koel Dutta Chowdhury and Cristina Espa{\~n}a-Bonet and Josef van Genabith},
url = {https://aclanthology.org/2021.ranlp-1.43/},
year = {2021},
date = {2021},
booktitle = {Proceedings of Recent Advances in Natural Language Processing (RANLP 2021)},
issn = {2603-2813},
pages = {380-390},
address = {Online},
abstract = {Previous research has used linguistic features to show that translations exhibit traces of source language interference and that phylogenetic trees between languages can be reconstructed from the results of translations into the same language. Recent research has shown that instances of translationese (source language interference) can even be detected in embedding spaces, comparing embeddings spaces of original language data with embedding spaces resulting from translations into the same language, using a simple Eigenvectorbased divergence from isomorphism measure. To date, it remains an open question whether alternative graph-isomorphism measures can produce better results. In this paper, we (i) explore Gromov-Hausdorff distance, (ii) present a novel spectral version of the Eigenvectorbased method, and (iii) evaluate all approaches against a broad linguistic typological database (URIEL). We show that language distances resulting from our spectral isomorphism approaches can reproduce genetic trees on a par with previous work without requiring any explicit linguistic information and that the results can be extended to non-Indo-European languages. Finally, we show that the methods are robust under a variety of modeling conditions.},
pubstate = {published},
type = {inproceedings}
}

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@miscellaneous{Menzel2021epic,
title = {EPIC-UdS - ein mehrsprachiges Korpus als Grundlage f{\"u}r die korpusbasierte Dolmetsch- und {\"U}bersetzungswissenschaft},
author = {Katrin Menzel and Heike Przybyl and Ekaterina Lapshinova-Koltunski},
year = {2021},
date = {2021},
booktitle = {TRANSLATA IV - 4. Internationale Konferenz zur Translationswissenschaft},
address = {Innsbruck},
pubstate = {published},
type = {miscellaneous}
}

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Fine-tuning pre-trained transformer-based language models such as BERT has become a common practice dominating leaderboards across various NLP benchmarks. Despite the strong empirical performance of fine-tuned models, fine-tuning is an unstable process: training the same model with multiple random seeds can result in a large variance of the task performance. Previous literature (Devlin et al., 2019; Lee et al., 2020; Dodge et al., 2020) identified two potential reasons for the observed instability: catastrophic forgetting and small size of the fine-tuning datasets. In this paper, we show that both hypotheses fail to explain the fine-tuning instability. We analyze BERT, RoBERTa, and ALBERT, fine-tuned on commonly used datasets from the GLUE benchmark, and show that the observed instability is caused by optimization difficulties that lead to vanishing gradients. Additionally, we show that the remaining variance of the downstream task performance can be attributed to differences in generalization where fine-tuned models with the same training loss exhibit noticeably different test performance. Based on our analysis, we present a simple but strong baseline that makes fine-tuning BERT-based models significantly more stable than the previously proposed approaches.

• https://arxiv.org/abs/2006.04884

@inproceedings{mosbach2021on,
title = {On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines},
author = {Marius Mosbach and Maksym Andriushchenko and Dietrich Klakow},
url = {https://arxiv.org/abs/2006.04884},
year = {2021},
date = {2021},
booktitle = {International Conference on Learning Representations},
abstract = {Fine-tuning pre-trained transformer-based language models such as BERT has become a common practice dominating leaderboards across various NLP benchmarks. Despite the strong empirical performance of fine-tuned models, fine-tuning is an unstable process: training the same model with multiple random seeds can result in a large variance of the task performance. Previous literature (Devlin et al., 2019; Lee et al., 2020; Dodge et al., 2020) identified two potential reasons for the observed instability: catastrophic forgetting and small size of the fine-tuning datasets. In this paper, we show that both hypotheses fail to explain the fine-tuning instability. We analyze BERT, RoBERTa, and ALBERT, fine-tuned on commonly used datasets from the GLUE benchmark, and show that the observed instability is caused by optimization difficulties that lead to vanishing gradients. Additionally, we show that the remaining variance of the downstream task performance can be attributed to differences in generalization where fine-tuned models with the same training loss exhibit noticeably different test performance. Based on our analysis, we present a simple but strong baseline that makes fine-tuning BERT-based models significantly more stable than the previously proposed approaches.},
pubstate = {published},
type = {inproceedings}
}

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The disambiguation and processing of coherence relations is often investigated with a focus on explicit connectives, such as but or so. Other, non-connective cues from the context also facilitate discourse inferences, although their precise disambiguating role and interaction with connectives have been largely overlooked in the psycholinguistic literature so far. This study reports on two crowdsourcing experiments that test the role of contextual cues (parallelism, antonyms, resultative verbs) in the disambiguation of contrast and consequence relations. We compare the effect of contextual cues in conceptually different relations, and with connectives that differ in their semantic precision. Using offline tasks, our results show that contextual cues significantly help disambiguating contrast and consequence relations in the absence of connectives. However, when connectives are present in the context, the effect of cues only holds if the connective is acceptable in the target relation. Overall, our study suggests that cues are decisive on their own, but only secondary in the presence of connectives. These results call for further investigation of the complex interplay between connective types, contextual cues, relation types and other linguistic and cognitive factors.

• pc.20003.cri     (0.43MB)
• https://www.jbe-platform.com/content/journals/10.1075/pc.20003.cri
• https://doi.org/10.1075/pc.20003.cri

@article{Crible2021,
title = {The role of non-connective discourse cues and their interaction with connectives},
author = {Ludivine Crible and Vera Demberg},
url = {https://www.jbe-platform.com/content/journals/10.1075/pc.20003.cri},
doi = {https://doi.org/10.1075/pc.20003.cri},
year = {2021},
date = {2021},
journal = {Pragmatics & Cognition},
pages = {313 - 338},
volume = {27},
number = {2},
abstract = {The disambiguation and processing of coherence relations is often investigated with a focus on explicit connectives, such as but or so. Other, non-connective cues from the context also facilitate discourse inferences, although their precise disambiguating role and interaction with connectives have been largely overlooked in the psycholinguistic literature so far. This study reports on two crowdsourcing experiments that test the role of contextual cues (parallelism, antonyms, resultative verbs) in the disambiguation of contrast and consequence relations. We compare the effect of contextual cues in conceptually different relations, and with connectives that differ in their semantic precision. Using offline tasks, our results show that contextual cues significantly help disambiguating contrast and consequence relations in the absence of connectives. However, when connectives are present in the context, the effect of cues only holds if the connective is acceptable in the target relation. Overall, our study suggests that cues are decisive on their own, but only secondary in the presence of connectives. These results call for further investigation of the complex interplay between connective types, contextual cues, relation types and other linguistic and cognitive factors.},
pubstate = {published},
type = {article}
}

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Speakers adapt their speech to increase clarity in the presence of back-ground noise (Lombard speech) [1, 2]. However, they also modify their speech tobe efficient by shortening word duration in more predictable contexts [3]. To meetthese two communicative functions, speakers will attempt to resolve any conflicting communicative demands. The present study focuses on how this can be resolvedin the acoustic domain. A total of 1520 target CV syllables were annotated andanalysed from 38 German speakers in 2 white-noise (no noise vs. -10 dB SNR) and 2 surprisal (H vs. L) contexts. Median fundamental frequency (F0), intensityrange, and syllable duration were extracted. Our results revealed effects of bothnoise and surprisal on syllable duration and intensity range, but only an effect ofnoise on F0. This might suggest redundant (multi-dimensional) acoustic coding in Lombard speech modification, but not so in surprisal modification.

• 2021_185_191     (1.04MB)
• https://www.essv.de/paper.php?id=1117

@inproceedings{Ibrahim2021,
title = {The effect of Lombard speech modifications in different information density contexts},
author = {Omnia Ibrahim and Ivan Yuen and Marjolein van Os and Bistra Andreeva and Bernd M{\"o}bius},
url = {https://www.essv.de/paper.php?id=1117},
year = {2021},
date = {2021},
booktitle = {Elektronische Sprachsignalverarbeitung 2021, Tagungsband der 32. Konferenz (Berlin)},
pages = {185-191},
publisher = {TUDpress},
address = {Dresden},
abstract = {Speakers adapt their speech to increase clarity in the presence of back-ground noise (Lombard speech) [1, 2]. However, they also modify their speech tobe efficient by shortening word duration in more predictable contexts [3]. To meetthese two communicative functions, speakers will attempt to resolve any conflicting communicative demands. The present study focuses on how this can be resolvedin the acoustic domain. A total of 1520 target CV syllables were annotated andanalysed from 38 German speakers in 2 white-noise (no noise vs. -10 dB SNR) and 2 surprisal (H vs. L) contexts. Median fundamental frequency (F0), intensityrange, and syllable duration were extracted. Our results revealed effects of bothnoise and surprisal on syllable duration and intensity range, but only an effect ofnoise on F0. This might suggest redundant (multi-dimensional) acoustic coding in Lombard speech modification, but not so in surprisal modification.},
pubstate = {published},
type = {inproceedings}
}

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This paper summarizes the results of a Modified Rhyme Test conducted with masked stimuli to simulate two common types of hearing impairment: bilateral pulsatile and pure tinnitus. Two types of stimuli, meaningful German words (natural read speech and TTS output) differing in initial or final positioned minimal pairs were modified to correspond to six listening conditions. Results showed higher recognition scores for natural speech compared to synthetic and better intelligibility for pulsatile tinnitus noise over pure tone tinnitus. These insights are of relevance given the alarming rates of tinnitus in epidemiological reports.

• 15_kudera     (0.17MB)
• https://www.essv.de/paper.php?id=1129

@inproceedings{Kudera2021,
title = {Natural and synthetic speech comprehension in simulated tonal and pulsatile tinnitus: A pilot study},
author = {Jacek Kudera and Marjolein van Os and Bernd M{\"o}bius},
url = {https://www.essv.de/paper.php?id=1129},
year = {2021},
date = {2021},
booktitle = {Elektronische Sprachsignalverarbeitung 2021, Tagungsband der 32. Konferenz (Berlin)},
pages = {273-280},
publisher = {TUDpress},
address = {Dresden},
abstract = {This paper summarizes the results of a Modified Rhyme Test conducted with masked stimuli to simulate two common types of hearing impairment: bilateral pulsatile and pure tinnitus. Two types of stimuli, meaningful German words (natural read speech and TTS output) differing in initial or final positioned minimal pairs were modified to correspond to six listening conditions. Results showed higher recognition scores for natural speech compared to synthetic and better intelligibility for pulsatile tinnitus noise over pure tone tinnitus. These insights are of relevance given the alarming rates of tinnitus in epidemiological reports.},
pubstate = {published},
type = {inproceedings}
}

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This study contributes to a better understanding of reading intercomprehension as manifested in the intelligibility of East and South Slavic languages to Russian native speakers in contextualized cognate recognition experiments using Belarusian, Ukrainian, and Bulgarian stimuli. While the results mostly confirm the expected mutual intelligibility effects, we also register apparent processing difficulties in some of the cases. In search of an explanation, we examine the correlation of the experimentally obtained intercomprehension scores with various linguistic factors, which contribute to cognate intelligibility in a context, considering common predictors of intercomprehension associated with (i) morphology and orthography, (ii) lexis, and (iii) syntax.

• stengeriplusavgustinovat027     (0.49MB)
• https://www.dialog-21.ru/media/5547/stengeriplusavgustinovat027.pdf

@inproceedings{Stenger-dialog2021,
title = {On Slavic cognate recognition in context},
author = {Irina Stenger and Tania Avgustinova},
editor = {Vladimir P. Selegej et al.},
url = {https://www.dialog-21.ru/media/5547/stengeriplusavgustinovat027.pdf},
year = {2021},
date = {2021},
booktitle = {Computational Linguistics and Intellectual Technologies: Papers from the Annual International Conference ‘Dialogue’},
pages = {660-668},
address = {Moscow, Russia},
abstract = {This study contributes to a better understanding of reading intercomprehension as manifested in the intelligibility of East and South Slavic languages to Russian native speakers in contextualized cognate recognition experiments using Belarusian, Ukrainian, and Bulgarian stimuli. While the results mostly confirm the expected mutual intelligibility effects, we also register apparent processing difficulties in some of the cases. In search of an explanation, we examine the correlation of the experimentally obtained intercomprehension scores with various linguistic factors, which contribute to cognate intelligibility in a context, considering common predictors of intercomprehension associated with (i) morphology and orthography, (ii) lexis, and (iii) syntax.},
pubstate = {published},
type = {inproceedings}
}

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Receptive multilingualism is a multidimensional and multifactorial phenomenon that crucially depends on the mutual intelligibility of closely related languages. As a strategy, it predominantly capitalizes upon a dynamic integration of linguistic, communicative, contextual, and socio-cognitive aspects. Relevant linguistic determinants (especially linguistic distances) along with recognizable extra-linguistic influences (such as attitude and exposure) have recently enjoyed increased attention in the research community. In our online (web-based) intercomprehension experiments, we have observed learning effects that appear to be empirically associated with individual cognitive skills. For this study, we tested 185 Russian subjects in a written word recognition task which essentially involved cognate guessing in Belarusian, Bulgarian, Macedonian, Serbian, and Ukrainian. The subjects had to translate the stimuli presented online into their native language, i.e. Russian. To reveal implicit multilingual learnability, we correlate the obtained intercomprehension scores with the detected reaction times, taking into consideration the potential influence of the experiment rank on the reaction time too.

• https://ibl.bas.bg/wp-content/uploads/2021/06/Sbornik_s_dokladi_CONFIBL2021_tom_2_FINAL.pdf

@inproceedings{Stenger-CONFIBL2021,
title = {Multilingual learnability and reaction time in online Slavic intercomprehension experiments},
author = {Irina Stenger and Tania Avgustinova},
editor = {Svetla Koeva and Maksim Stamenov},
url = {https://ibl.bas.bg/wp-content/uploads/2021/06/Sbornik_s_dokladi_CONFIBL2021_tom_2_FINAL.pdf},
year = {2021},
date = {2021},
booktitle = {Proceedings of the International Annual Conference of the Institute for Bulgarian Language},
pages = {191-200},
publisher = {Marin Drinov Academic Publishers},
address = {Sofia, Bulgaria},
abstract = {Receptive multilingualism is a multidimensional and multifactorial phenomenon that crucially depends on the mutual intelligibility of closely related languages. As a strategy, it predominantly capitalizes upon a dynamic integration of linguistic, communicative, contextual, and socio-cognitive aspects. Relevant linguistic determinants (especially linguistic distances) along with recognizable extra-linguistic influences (such as attitude and exposure) have recently enjoyed increased attention in the research community. In our online (web-based) intercomprehension experiments, we have observed learning effects that appear to be empirically associated with individual cognitive skills. For this study, we tested 185 Russian subjects in a written word recognition task which essentially involved cognate guessing in Belarusian, Bulgarian, Macedonian, Serbian, and Ukrainian. The subjects had to translate the stimuli presented online into their native language, i.e. Russian. To reveal implicit multilingual learnability, we correlate the obtained intercomprehension scores with the detected reaction times, taking into consideration the potential influence of the experiment rank on the reaction time too.},
pubstate = {published},
type = {inproceedings}
}

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