Publications

Degaetano-Ortlieb, Stefania

Measuring informativity: The rise of compounds as informationally dense structures in 20th century Scientific English Book Chapter

Soave, Elena; Biber, Douglas (Ed.): Corpus Approaches to Register Variation, Studies in Corpus Linguistics, 103, John Benjamins Publishing Company, pp. 291-312, 2021.

By applying data-driven methods based on information theory, this study adds to previous work on the development of the scientific register by measuring the informativity of alternative phrasal structures shown to be involved in change in language use in 20th-century Scientific English. The analysis based on data-driven periodization shows compounds to be distinctive grammatical structures from the 1920s onwards in Proceedings A of the Royal Society of London. Compounds not only increase in frequency, but also show higher informativity than their less dense prepositional counterparts. Results also show that the lower the informativity of particular items, the more alternative, more informationally dense options might be favoured (e.g., of-phrases vs. compounds) – striving for communicative efficiency thus being one force shaping the scientific register.

@inbook{Degaetano-Ortlieb2021,
title = {Measuring informativity: The rise of compounds as informationally dense structures in 20th century Scientific English},
author = {Stefania Degaetano-Ortlieb},
editor = {Elena Soave and Douglas Biber},
url = {https://benjamins.com/catalog/scl.103.11deg},
doi = {https://doi.org/10.1075/scl.103.11deg},
year = {2021},
date = {2021},
booktitle = {Corpus Approaches to Register Variation},
pages = {291-312},
publisher = {John Benjamins Publishing Company},
abstract = {By applying data-driven methods based on information theory, this study adds to previous work on the development of the scientific register by measuring the informativity of alternative phrasal structures shown to be involved in change in language use in 20th-century Scientific English. The analysis based on data-driven periodization shows compounds to be distinctive grammatical structures from the 1920s onwards in Proceedings A of the Royal Society of London. Compounds not only increase in frequency, but also show higher informativity than their less dense prepositional counterparts. Results also show that the lower the informativity of particular items, the more alternative, more informationally dense options might be favoured (e.g., of-phrases vs. compounds) – striving for communicative efficiency thus being one force shaping the scientific register.},
pubstate = {published},
type = {inbook}
}

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Project:   B1

Bizzoni, Yuri; Degaetano-Ortlieb, Stefania; Menzel, Katrin; Teich, Elke

The diffusion of scientific terms - tracing individuals' influence in the history of science for English Inproceedings

Proceedings of the 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, Association for Computational Linguistics, pp. 120-127, Punta Cana, Dominican Republic (online), 2021.

Tracing the influence of individuals or groups in social networks is an increasingly popular task in sociolinguistic studies. While methods to determine someone’s influence in shortterm contexts (e.g., social media, on-line political debates) are widespread, influence in longterm contexts is less investigated and may be harder to capture. We study the diffusion of scientific terms in an English diachronic scientific corpus, applying Hawkes Processes to capture the role of individual scientists as „influencers“ or „influencees“ in the diffusion of new concepts. Our findings on two major scientific discoveries in chemistry and astronomy of the 18th century reveal that modelling both the introduction and diffusion of scientific terms in a historical corpus as Hawkes Processes allows detecting patterns of influence between authors on a long-term scale.

@inproceedings{bizzoni-etal-2021-diffusion,
title = {The diffusion of scientific terms - tracing individuals' influence in the history of science for English},
author = {Yuri Bizzoni and Stefania Degaetano-Ortlieb and Katrin Menzel and Elke Teich},
url = {https://aclanthology.org/2021.latechclfl-1.14},
doi = {https://doi.org/10.18653/v1/2021.latechclfl-1.14},
year = {2021},
date = {2021-11-30},
booktitle = {Proceedings of the 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature},
pages = {120-127},
publisher = {Association for Computational Linguistics},
address = {Punta Cana, Dominican Republic (online)},
abstract = {Tracing the influence of individuals or groups in social networks is an increasingly popular task in sociolinguistic studies. While methods to determine someone's influence in shortterm contexts (e.g., social media, on-line political debates) are widespread, influence in longterm contexts is less investigated and may be harder to capture. We study the diffusion of scientific terms in an English diachronic scientific corpus, applying Hawkes Processes to capture the role of individual scientists as "influencers" or "influencees" in the diffusion of new concepts. Our findings on two major scientific discoveries in chemistry and astronomy of the 18th century reveal that modelling both the introduction and diffusion of scientific terms in a historical corpus as Hawkes Processes allows detecting patterns of influence between authors on a long-term scale.},
pubstate = {published},
type = {inproceedings}
}

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Project:   B1

Voigtmann, Sophia; Speyer, Augustin

Information density and the extraposition of German relative clauses Journal Article

Frontiers in Psychology, pp. 1-18, 2021.

This paper aims to find a correlation between Information Density (ID) and extraposition of Relative Clauses (RC) in Early New High German. Since surprisal is connected to perceiving difficulties, the impact on the working memory is lower for frequent combinations with low surprisal-values than it is for rare combinations with higher surprisal-values. To improve text comprehension, producers therefore distribute information as evenly as possible across a discourse. Extraposed RC are expected to have a higher surprisal-value than embedded RC. We intend to find evidence for this idea in RC taken from scientific texts from the 17th to 19th century. We built a corpus of tokenized, lemmatized and normalized papers about medicine from the 17th and 19th century, manually determined the RC-variants and calculated a skipgram-Language Model to compute the 2-Skip-bigram surprisal of every word of the relevant sentences. A logistic regression over the summed up surprisal values shows a significant result, which indicates a correlation between surprisal values and extraposition. So, for these periods it can be said that RC are more likely to be extraposed when they have a high total surprisal value. The influence of surprisal values also seems to be stable across time. The comparison of the analyzed language periods shows no significant change.

@article{Voigtmann.Speyer,
title = {Information density and the extraposition of German relative clauses},
author = {Sophia Voigtmann and Augustin Speyer},
url = {https://doi.org/10.3389/fpsyg.2021.650969},
doi = {https://doi.org/10.3389/fpsyg.2021.650969},
year = {2021},
date = {2021-11-26},
journal = {Frontiers in Psychology},
pages = {1-18},
abstract = {This paper aims to find a correlation between Information Density (ID) and extraposition of Relative Clauses (RC) in Early New High German. Since surprisal is connected to perceiving difficulties, the impact on the working memory is lower for frequent combinations with low surprisal-values than it is for rare combinations with higher surprisal-values. To improve text comprehension, producers therefore distribute information as evenly as possible across a discourse. Extraposed RC are expected to have a higher surprisal-value than embedded RC. We intend to find evidence for this idea in RC taken from scientific texts from the 17th to 19th century. We built a corpus of tokenized, lemmatized and normalized papers about medicine from the 17th and 19th century, manually determined the RC-variants and calculated a skipgram-Language Model to compute the 2-Skip-bigram surprisal of every word of the relevant sentences. A logistic regression over the summed up surprisal values shows a significant result, which indicates a correlation between surprisal values and extraposition. So, for these periods it can be said that RC are more likely to be extraposed when they have a high total surprisal value. The influence of surprisal values also seems to be stable across time. The comparison of the analyzed language periods shows no significant change.},
pubstate = {published},
type = {article}
}

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Project:   C6

Menzel, Katrin; Krielke, Marie-Pauline; Degaetano-Ortlieb, Stefania

Structural complexity in scientific journal articles across time - from negative clausal expressions towards adjectival negative prefixes Inproceedings

Workshop on Complexity and Register (CAR21), Berlin, Germany, CRC1412 Register, 2021.

@inproceedings{Menzel-etal2021,
title = {Structural complexity in scientific journal articles across time - from negative clausal expressions towards adjectival negative prefixes},
author = {Katrin Menzel and Marie-Pauline Krielke and Stefania Degaetano-Ortlieb},
year = {2021},
date = {2021-11-19},
booktitle = {Workshop on Complexity and Register (CAR21)},
address = {Berlin, Germany, CRC1412 Register},
pubstate = {published},
type = {inproceedings}
}

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Project:   B1

Menzel, Katrin

Scientific Eponyms throughout the History of English Scholarly Journal Articles Book Chapter

Van de Velde, Hans; Dolezal, Fredric T.;  (Ed.): Broadening Perspectives in the History of Dictionaries and Word Studies, Cambridge Scholars Publishing, pp. 159-193, Newcastle upon Tyne, 2021, ISBN 1-5275-7432-6.

@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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Project:   B1

Häuser, Katja; Kray, Jutta

How odd: Diverging effects of predictability and plausibility on online sentence processing and subsequent word recognition Inproceedings

Poster presentation at AMLaP 2021: Architectures and Mechanisms for Language Processing, September 2-4, 2021.

@inproceedings{haeuserkray2021b,
title = {How odd: Diverging effects of predictability and plausibility on online sentence processing and subsequent word recognition},
author = {Katja H{\"a}user and Jutta Kray},
url = {https://amlap2021.github.io/program/30.pdf},
year = {2021},
date = {2021},
booktitle = {Poster presentation at AMLaP 2021: Architectures and Mechanisms for Language Processing, September 2-4},
pubstate = {published},
type = {inproceedings}
}

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Project:   A5

Staudte, Maria; Ankener, Christine; Drenhaus, Heiner; Crocker, Matthew W.

Graded expectations in visually situated comprehension: Costs and benefits as indexed by the N400 Journal Article

Psychonomic Bulletin & Review, 28, Springer, pp. 624-631, 2021.

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.

@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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Project:   A5

Höltje, Gerrit; Mecklinger, Axel

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 Miscellaneous

CNS 2020 Virtual meeting, Abstract Book, 2021.

@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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Project:   A6

Degaetano-Ortlieb, Stefania; Säily, Tanja; Bizzoni, Yuri

Registerial Adaptation vs. Innovation Across Situational Contexts: 18th Century Women in Transition Journal Article

Frontiers in Artificial Intelligence, section Language and Computation, 4, pp. 56, 2021.

@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},
pages = {56},
volume = {4},
pubstate = {published},
type = {article}
}

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Project:   B1

Bizzoni, Yuri; Lapshinova-Koltunski, Ekaterina

Measuring Translationese across Levels of Expertise: Are Professionals more Surprising than Students? Inproceedings

Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa), Linköping University Electronic Press, Sweden, pp. 53-63, 2021.

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.

@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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Project:   B7

Aurnhammer, Christoph; Delogu, Francesca; Schulz, Miriam; Brouwer, Harm; Crocker, Matthew W.

Retrieval (N400) and Integration (P600) in Expectation-based Comprehension Journal Article

PLoS ONE, 16, pp. e0257430, 2021.

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.

@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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Project:   A1

Demberg, Vera; Torabi Asr, Fatemeh; Scholman, Merel

DiscAlign for Penn and RST Discourse Treebanks Miscellaneous

Linguistic Data Consortium, Philadelphia, 2021, ISBN 1-58563-975-3.

@miscellaneous{Demberg_etal_DiscAlign,
title = {DiscAlign for Penn and RST Discourse Treebanks},
author = {Vera Demberg and Fatemeh Torabi Asr and Merel Scholman},
doi = {https://doi.org/10.35111/cf0q-c454},
year = {2021},
date = {2021-09-15},
isbn = {1-58563-975-3},
publisher = {Linguistic Data Consortium},
address = {Philadelphia},
pubstate = {published},
type = {miscellaneous}
}

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Project:   B2

Krielke, Marie-Pauline

Relativizers as markers of grammatical complexity: A diachronic, cross-register study of English and German Journal Article

Bergen Language and Linguistics Studies, 11, pp. 91-120, 2021.

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.

@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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Project:   B1

Bhandari, Pratik; Demberg, Vera; Kray, Jutta

Semantic Predictability Facilitates Comprehension of Degraded Speech in a Graded Manner Journal Article

Frontiers in Psychology, Frontiers, pp. 3769, 2021.

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.

@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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Project:   A4

Ortmann, Katrin

Automatic Phrase Recognition in Historical German Inproceedings

Proceedings of the 17th Conference on Natural Language Processing (KONVENS 2021), KONVENS 2021 Organizers, Düsseldorf, Germany, 2021.

@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)},
publisher = {KONVENS 2021 Organizers},
address = {D{\"u}sseldorf, Germany},
pubstate = {published},
type = {inproceedings}
}

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Project:   C6

Mosbach, Marius; Stenger, Irina; Avgustinova, Tania; Möbius, Bernd; Klakow, Dietrich

incom.py 2.0 - Calculating Linguistic Distances and Asymmetries in Auditory Perception of Closely Related Languages Inproceedings

Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021), INCOMA Ltd., pp. 968-977, Held Online, 2021.

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.

@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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Projects:   B4 C4

Pylypenko, Daria; Amponsah-Kaakyire, Kwabena; Dutta Chowdhury, Koel; van Genabith, Josef; España i Bonet, Cristina

Comparing Feature-Engineering and Feature-Learning Approaches for Multilingual Translationese Classification Inproceedings Forthcoming

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), Online and in the Dominican Republic, 2021.

@inproceedings{Pylypenko2021comparing,
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 i Bonet},
year = {2021},
date = {2021},
booktitle = {Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
address = {Online and in the Dominican Republic},
pubstate = {forthcoming},
type = {inproceedings}
}

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Project:   B6

Dutta Chowdhury, Koel; España i Bonet, Cristina; van Genabith, Josef

Tracing Source Language Interference in Translation with Graph-Isomorphism Measures Inproceedings

Proceedings of Recent Advances in Natural Language Processing (RANLP 2021), pp. 380-390, Online, 2021, ISSN 2603-2813.

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.

@inproceedings{Chowdhury2021tracing,
title = {Tracing Source Language Interference in Translation with Graph-Isomorphism Measures},
author = {Koel Dutta Chowdhury and Cristina Espa{\~n}a i 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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Project:   B6

Menzel, Katrin; Przybyl, Heike; Lapshinova-Koltunski, Ekaterina

EPIC-UdS - ein mehrsprachiges Korpus als Grundlage für die korpusbasierte Dolmetsch- und Übersetzungswissenschaft Miscellaneous Forthcoming

TRANSLATA IV - 4. Internationale Konferenz zur Translationswissenschaft, Innsbruck, 2021.

@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 = {forthcoming},
type = {miscellaneous}
}

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Project:   B7

Mosbach, Marius; Andriushchenko, Maksym; Klakow, Dietrich

On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines Inproceedings

International Conference on Learning Representations, 2021.

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.

@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://openreview.net/forum?id=nzpLWnVAyah},
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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Project:   B4

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