Publications

From antiquity to the modern era, translations have contributed to the production and circulation of scientific knowledge. From the time when the first English scientific journals began to appear in the mid-17th century, English translations of scientific texts by non-English-speaking authors began to appear in these journals. This paper highlights some aspects with regard to translations of scientific texts published in journals from the Royal Society of London between the 17th and the 20th century. The dataset used for the case study is the Royal Society Corpus (RSC) 6.0 / 7.0. Translations for the Royal Society journals were often produced by Fellows or secretaries of the Royal Society. Most translated articles found in the corpus were published in the Philosophical Transactions during the 18th century as translations from French. Overall, the translations in the RSC are characterised by domesticating practices.

• Festschrift_Teich_Menzel     (0.13MB)
• https://www.uni-saarland.de/fileadmin/upload/lehrstuhl/teich/degaetano/Festschrift_Teich_Menzel.pdf

@miscellaneous{Festschrift_Teich_Menzel,
title = {Translated texts in the Philosophical Transactions and Proceedings of the Royal Society from the 17th to the 20th century},
author = {Katrin Menzel},
url = {https://www.uni-saarland.de/fileadmin/upload/lehrstuhl/teich/degaetano/Festschrift_Teich_Menzel.pdf},
year = {2023},
date = {2023},
booktitle = {Online-Festschrift for Elke Teich on the Occasion of her 60th birthday},
address = {Saarland University},
abstract = {From antiquity to the modern era, translations have contributed to the production and circulation of scientific knowledge. From the time when the first English scientific journals began to appear in the mid-17th century, English translations of scientific texts by non-English-speaking authors began to appear in these journals. This paper highlights some aspects with regard to translations of scientific texts published in journals from the Royal Society of London between the 17th and the 20th century. The dataset used for the case study is the Royal Society Corpus (RSC) 6.0 / 7.0. Translations for the Royal Society journals were often produced by Fellows or secretaries of the Royal Society. Most translated articles found in the corpus were published in the Philosophical Transactions during the 18th century as translations from French. Overall, the translations in the RSC are characterised by domesticating practices.},
pubstate = {published},
type = {miscellaneous}
}

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• PaPE (1)     (0.92MB)
• https://www.researchgate.net/publication/371138687_The_interplay_between_syllable-based_predictability_and_voicing_during_closure_in_intersonorant_German_stops

@inproceedings{inproceedings,
title = {The interplay between syllable-based predictability and voicing during closure in intersonorant German stops},
author = {Omnia Ibrahim and Ivan Yuen and Bistra Andreeva and Bernd M{\"o}bius},
url = {https://www.researchgate.net/publication/371138687_The_interplay_between_syllable-based_predictability_and_voicing_during_closure_in_intersonorant_German_stops},
year = {2023},
date = {2023},
booktitle = {Conference: Phonetics and Phonology in Europe 2023 (PaPE 2023)},
address = {Nijmegen, the Netherlands},
abstract = {

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Mit dem Konzept “Easy-to-read” werden Teilsysteme natürlicher Sprachen bezeichnet, welche durch eine systematische Reduktion auf den Ebenen Lexik und Syntax entstehen und den Zugang zu geschriebenen Informationen für Erwachsene mit geringen Lesekompetenzen gewährleisten. Im Deutschen gibt es “Leichte Sprache”, welche sich nach spezifischen linguistischen und typografischen Regeln richtet, und die weniger restringierte “einfache Sprache”. Beide Varianten erhalten im akademischen sowie nicht-akademischen Diskurs vermehrt Aufmerksamkeit – nicht zuletzt dank der im Jahr 2009 in Deutschland ratifizierten UN-Behindertenrechtskonvention (UN-BRK).

• 5_Jablotschkin_Zinsmeister_LeiKo     (0.32MB)
• https://www.ids-mannheim.de/fileadmin/aktuell/Jahrestagungen/2022/Methodenmesse/5_Jablotschkin_Zinsmeister_LeiKo.pdf

@incollection{jablotschkin_zinsmeister_2023,
title = {LeiKo. Ein Vergleichskorpus f{\"u}r Leichte Sprache und Einfache Sprache},
author = {Sarah Jablotschkin and Heike Zinsmeister},
url = {https://www.ids-mannheim.de/fileadmin/aktuell/Jahrestagungen/2022/Methodenmesse/5_Jablotschkin_Zinsmeister_LeiKo.pdf},
year = {2023},
date = {2023},
booktitle = {Neue Entwicklungen in der Korpuslandschaft der Germanistik. Beitr{\"a}ge zur IDS-Methodenmesse 2022},
publisher = {Kupietz, Mark und Thomas Schmidt},
address = {T{\"u}bingen: Narr},
abstract = {Mit dem Konzept “Easy-to-read” werden Teilsysteme nat{\"u}rlicher Sprachen bezeichnet, welche durch eine systematische Reduktion auf den Ebenen Lexik und Syntax entstehen und den Zugang zu geschriebenen Informationen f{\"u}r Erwachsene mit geringen Lesekompetenzen gew{\"a}hrleisten. Im Deutschen gibt es “Leichte Sprache”, welche sich nach spezifischen linguistischen und typografischen Regeln richtet, und die weniger restringierte “einfache Sprache”. Beide Varianten erhalten im akademischen sowie nicht-akademischen Diskurs vermehrt Aufmerksamkeit – nicht zuletzt dank der im Jahr 2009 in Deutschland ratifizierten UN-Behindertenrechtskonvention (UN-BRK).},
pubstate = {published},
type = {incollection}
}

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This poster presents our evaluation of a neural coreference resolver (Schröder et al. 2021) on simplified German texts as well as the results of an annotation study that we conducted in order to analyse error sources.

The underlying corpus can be found on Zenodo: https://doi.org/10.5281/zenodo.3626763

• DGfS_2023_Poster_LeiKo_c2f_Evaluation     (1.7MB)
• https://doi.org/10.25592/uhhfdm.12252
• https://doi.org/10.25592/uhhfdm.12252

@conference{jablotschkin_sarah_2023_12252,
title = {Evaluation of neural coreference annotation of simplified German},
author = {Sarah Jablotschkin and Nele Benz and Heike Zinsmeister},
url = {https://doi.org/10.25592/uhhfdm.12252},
doi = {https://doi.org/10.25592/uhhfdm.12252},
year = {2023},
date = {2023},
booktitle = {Posterpr{\"a}sentation auf der Computational Linguistics Poster Session im Rahmen der 45. Jahrestagung der Deutschen Gesellschaft f{\"u}r Sprachwissenschaft (DGfS) in K{\"o}ln},
abstract = {This poster presents our evaluation of a neural coreference resolver (Schr{\"o}der et al. 2021) on simplified German texts as well as the results of an annotation study that we conducted in order to analyse error sources. The underlying corpus can be found on Zenodo: https://doi.org/10.5281/zenodo.3626763},
pubstate = {forthcoming},
type = {conference}
}

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In this replication study of previous research into dependency length minimisation (DLM), we pilot a new parallel multilingual parsed corpus to examine whether previous findings are upheld when controlling for variation in domain and sentence content between languages. We follow the approach of previous research in comparing the dependency lengths of observed sentences in a multilingual corpus to a variety of baselines: permutations of the sentences, either random or according to some fixed schema. We go on to compare DLM with intervener complexity measure (ICM), an alternative measure of syntactic complexity. Our findings uphold both dependency length and intervener complexity minimisation in all languages under investigation. We also find a markedly lesser extent of dependency length minimisation in verbfinal languages, and the same for intervener complexity measure. We conclude that dependency length and intervener complexity minimisation as universals are upheld when controlling for domain and content variation, but that further research is needed into the asymmetry between verb-final and other languages in this regard.

• 20_revisiting_dependency_length_a     (0.31MB)
• https://aclanthology.org/2023.sigtyp-1.11/

@inproceedings{dyer-2023-revisiting,
title = {Revisiting dependency length and intervener complexity minimisation on a parallel corpus in 35 languages},
author = {Andrew Dyer},
url = {https://aclanthology.org/2023.sigtyp-1.11/},
year = {2023},
date = {2023},
booktitle = {Proceedings of the 5th Workshop on Research in Computational Linguistic Typology and Multilingual NLP},
pages = {110-119},
publisher = {Association for Computational Linguistics},
address = {Dubrovnik, Croatia},
abstract = {

In this replication study of previous research into dependency length minimisation (DLM), we pilot a new parallel multilingual parsed corpus to examine whether previous findings are upheld when controlling for variation in domain and sentence content between languages. We follow the approach of previous research in comparing the dependency lengths of observed sentences in a multilingual corpus to a variety of baselines: permutations of the sentences, either random or according to some fixed schema. We go on to compare DLM with intervener complexity measure (ICM), an alternative measure of syntactic complexity. Our findings uphold both dependency length and intervener complexity minimisation in all languages under investigation. We also find a markedly lesser extent of dependency length minimisation in verbfinal languages, and the same for intervener complexity measure. We conclude that dependency length and intervener complexity minimisation as universals are upheld when controlling for domain and content variation, but that further research is needed into the asymmetry between verb-final and other languages in this regard.

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Behavioral studies have shown that speaker gaze to objects in a co-present scene can influence listeners’ expectations about how the utterance will unfold. These findings have recently been supported by ERP studies that linked the underlying mechanisms of the integration of speaker gaze with an utterance meaning representation to multiple ERP components. This leads to the question, however, as to whether speaker gaze should be considered part of the communicative signal itself, such that the referential information conveyed by gaze can help listeners not only form expectations but also to confirm referential expectations induced by the prior linguistic context. In the current study, we investigated this question by conducting an ERP experiment (N=24, Age:[19,31]), in which referential expectations were established by linguistic context together with several depicted objects in the scene. Those expectations then could be confirmed by subsequent speaker gaze that preceded the referential expression. Participants were presented with a centrally positioned face performing gaze actions aligned to utterances comparing two out of three displayed objects, with the task to judge whether the sentence was true given the provided scene. We manipulated the gaze cue to be either Present (toward the subsequently named object) or Absent preceding contextually Expected or Unexpected referring nouns. The results provided strong evidence for gaze as being treated as an integral part of the communicative signal: While in the absence of gaze, effects of phonological verification (PMN), word meaning retrieval (N400) and sentence meaning integration/evaluation (P600) were found on the unexpected noun, in the presence of gaze effects of retrieval (N400) and integration/evaluation (P300) were solely found in response to the pre-referent gaze cue when it was directed toward the unexpected referent with attenuated effects on the following referring noun.

• https://www.sciencedirect.com/science/article/pii/S0010027723000835?via%3Dihub
• https://doi.org/10.1016/j.cognition.2023.105449

@article{Jachmannetal-23,
title = {When a look is enough: Neurophysiological correlates of referential speaker gaze in situated comprehension},
author = {Torsten Jachmann and Heiner Drenhaus and Maria Staudte and Matthew W. Crocker},
url = {https://www.sciencedirect.com/science/article/pii/S0010027723000835?via%3Dihub},
doi = {https://doi.org/10.1016/j.cognition.2023.105449},
year = {2023},
date = {2023},
journal = {Cognition},
pages = {105449},
volume = {236},
abstract = {Behavioral studies have shown that speaker gaze to objects in a co-present scene can influence listeners’ expectations about how the utterance will unfold. These findings have recently been supported by ERP studies that linked the underlying mechanisms of the integration of speaker gaze with an utterance meaning representation to multiple ERP components. This leads to the question, however, as to whether speaker gaze should be considered part of the communicative signal itself, such that the referential information conveyed by gaze can help listeners not only form expectations but also to confirm referential expectations induced by the prior linguistic context. In the current study, we investigated this question by conducting an ERP experiment (N=24, Age:[19,31]), in which referential expectations were established by linguistic context together with several depicted objects in the scene. Those expectations then could be confirmed by subsequent speaker gaze that preceded the referential expression. Participants were presented with a centrally positioned face performing gaze actions aligned to utterances comparing two out of three displayed objects, with the task to judge whether the sentence was true given the provided scene. We manipulated the gaze cue to be either Present (toward the subsequently named object) or Absent preceding contextually Expected or Unexpected referring nouns. The results provided strong evidence for gaze as being treated as an integral part of the communicative signal: While in the absence of gaze, effects of phonological verification (PMN), word meaning retrieval (N400) and sentence meaning integration/evaluation (P600) were found on the unexpected noun, in the presence of gaze effects of retrieval (N400) and integration/evaluation (P300) were solely found in response to the pre-referent gaze cue when it was directed toward the unexpected referent with attenuated effects on the following referring noun.},
pubstate = {published},
type = {article}
}

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Disagreement in natural language annotation has mostly been studied from a perspective of biases introduced by the annotators and the annotation frameworks. Here, we propose to analyze another source of bias: task design bias, which has a particularly strong impact on crowdsourced linguistic annotations where natural language is used to elicit the interpretation of laymen annotators. For this purpose we look at implicit discourse relation annotation, a task that has repeatedly been shown to be difficult due to the relations‘ ambiguity. We compare the annotations of 1,200 discourse relations obtained using two distinct annotation tasks and quantify the biases of both methods across four different domains. Both methods are natural language annotation tasks designed for crowdsourcing. We show that the task design can push annotators towards certain relations and that some discourse relations senses can be better elicited with one or the other annotation approach. We also conclude that this type of bias should be taken into account when training and testing models.

• 2304.00815     (0.44MB)
• https://arxiv.org/abs/2304.00815

@article{Pyatkinetal.,
title = {Design Choices for Crowdsourcing Implicit Discourse Relations: Revealing the Biases introduced by Task Design},
author = {Valentina Pyatkin and Frances Pik Yu Yung and Merel Scholman and Reut Tsarfaty and Ido Dagan and Vera Demberg},
url = {https://arxiv.org/abs/2304.00815},
year = {2023},
date = {2023},
journal = {Transactions of the Association for Computational Linguistics (TACL)},
abstract = {Disagreement in natural language annotation has mostly been studied from a perspective of biases introduced by the annotators and the annotation frameworks. Here, we propose to analyze another source of bias: task design bias, which has a particularly strong impact on crowdsourced linguistic annotations where natural language is used to elicit the interpretation of laymen annotators. For this purpose we look at implicit discourse relation annotation, a task that has repeatedly been shown to be difficult due to the relations' ambiguity. We compare the annotations of 1,200 discourse relations obtained using two distinct annotation tasks and quantify the biases of both methods across four different domains. Both methods are natural language annotation tasks designed for crowdsourcing. We show that the task design can push annotators towards certain relations and that some discourse relations senses can be better elicited with one or the other annotation approach. We also conclude that this type of bias should be taken into account when training and testing models.},
pubstate = {published},
type = {article}
}

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The integration of word meaning into an unfolding utterance representation is a core operation of incremental language comprehension. There is considerable debate, however, as to which component of the ERP signal—the N400 or the P600—directly reflects integrative processes, with far reaching consequences for the temporal organization and architecture of the comprehension system. Multi-stream models maintaining the N400 as integration crucially rely on the presence of a semantically attractive plausible alternative interpretation to account for the absence of an N400 effect in response to certain semantic anomalies, as reported in previous studies. The single-stream Retrieval–Integration account posits the P600 as an index of integration, further predicting that its amplitude varies continuously with integrative effort. Here, we directly test these competing hypotheses using a context manipulation design in which a semantically attractive alternative is either available or not, and target word plausibility is varied across three levels. An initial self-paced reading study revealed graded reading times for plausibility, suggesting differential integration effort. A subsequent ERP study showed no N400 differences across conditions, and that P600 amplitude is graded for plausibility. These findings are inconsistent with the interpretation of the N400 as an index of integration, as no N400 effect emerged even in the absence of a semantically attractive alternative. By contrast, the link between plausibility, reading times, and P600 amplitude supports the view that the P600 is a continuous index of integration effort. More generally, our results support a single-stream architecture and eschew the need for multi-stream accounts.

• Psychophysiology - 2023 - Aurnhammer - The P600 as a continuous index of integration effort     (11.04MB)
• https://onlinelibrary.wiley.com/doi/10.1111/psyp.14302
• https://doi.org/10.1111/psyp.14302

@article{aurnhammer2023continuous,
title = {The P600 as a Continuous Index of Integration Effort},
author = {Christoph Aurnhammer and Francesca Delogu and Harm Brouwer and Matthew W. Crocker},
url = {https://onlinelibrary.wiley.com/doi/10.1111/psyp.14302},
doi = {https://doi.org/10.1111/psyp.14302},
year = {2023},
date = {2023},
journal = {Psychophysiology},
abstract = {The integration of word meaning into an unfolding utterance representation is a core operation of incremental language comprehension. There is considerable debate, however, as to which component of the ERP signal—the N400 or the P600—directly reflects integrative processes, with far reaching consequences for the temporal organization and architecture of the comprehension system. Multi-stream models maintaining the N400 as integration crucially rely on the presence of a semantically attractive plausible alternative interpretation to account for the absence of an N400 effect in response to certain semantic anomalies, as reported in previous studies. The single-stream Retrieval–Integration account posits the P600 as an index of integration, further predicting that its amplitude varies continuously with integrative effort. Here, we directly test these competing hypotheses using a context manipulation design in which a semantically attractive alternative is either available or not, and target word plausibility is varied across three levels. An initial self-paced reading study revealed graded reading times for plausibility, suggesting differential integration effort. A subsequent ERP study showed no N400 differences across conditions, and that P600 amplitude is graded for plausibility. These findings are inconsistent with the interpretation of the N400 as an index of integration, as no N400 effect emerged even in the absence of a semantically attractive alternative. By contrast, the link between plausibility, reading times, and P600 amplitude supports the view that the P600 is a continuous index of integration effort. More generally, our results support a single-stream architecture and eschew the need for multi-stream accounts.},
pubstate = {published},
type = {article}
}

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There is a long-standing controversy around the question of whether referent predictability affects pronominalization: while there are good theoretical reasons for this prediction (e.g., Arnold, 2008), the experimental evidence has been rather mixed. We here report on three highly powered studies that manipulate a range of factors that have differed between previous studies, in order to determine more exactly under which conditions a predictability effect on pronominalization can be found. We use a constrained as well as a free reference task, and manipulate verb type, antecedent ambiguity, length of NP and whether the stimuli are presented within a story context or not. Our results find the story context to be the single important factor that allows to elicit an effect of predictability on pronoun choice, in line with (Rosa and Arnold, 2017; Weatherford and Arnold, 2021). We also propose a parametrization for a rational speech act model, that reconciles the findings between many of the experiments in the literature.

• https://europepmc.org/article/MED/37265576

@article{Demberg.etal23,
title = {A systematic evaluation of factors affecting referring expression choice in passage completion tasks},
author = {Vera Demberg and Ekaterina Kravtchenko and Jia Loy},
url = {https://europepmc.org/article/MED/37265576},
year = {2023},
date = {2023},
journal = {Journal of Memory and Language, 130, 104413},
abstract = {There is a long-standing controversy around the question of whether referent predictability affects pronominalization: while there are good theoretical reasons for this prediction (e.g., Arnold, 2008), the experimental evidence has been rather mixed. We here report on three highly powered studies that manipulate a range of factors that have differed between previous studies, in order to determine more exactly under which conditions a predictability effect on pronominalization can be found. We use a constrained as well as a free reference task, and manipulate verb type, antecedent ambiguity, length of NP and whether the stimuli are presented within a story context or not. Our results find the story context to be the single important factor that allows to elicit an effect of predictability on pronoun choice, in line with (Rosa and Arnold, 2017; Weatherford and Arnold, 2021). We also propose a parametrization for a rational speech act model, that reconciles the findings between many of the experiments in the literature.},
pubstate = {published},
type = {article}
}

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The linguistic analysis of historical German and diachronic syntactic change is traditionally based on small, manually annotated data sets. As a consequence, such studies lack the generalizability and statistical significance that quantitative approaches can offer. In this thesis, computational methods for the automatic syntactic analysis of modern and historical German are developed, which help to overcome the natural limits of manual annotation and enable the creation of large annotated data sets. The main goal of the thesis is to identify extraposition in modern and historical German, with extraposition being defined as the movement of constituents from their base position to the post-field of the sentence (Höhle 2019; Wöllstein 2018). For the automatic recognition of extraposition, two annotation steps are combined: (i) a topological field analysis for the identification of post-fields and (ii) a constituency analysis to recognize candidates for extraposition. The thesis describes experiments on topological field parsing (Ortmann 2020), chunking (Ortmann 2021a), and constituency parsing (Ortmann 2021b). The best results are achieved with statistical models trained on Part-of-Speech tags as input. Contrary to previous studies, all annotation steps are thoroughly evaluated with the newly developed FairEval method for the fine-grained error analysis and fair evaluation of labeled spans (Ortmann 2022). In an example analysis, the created methods are applied to large collections of modern and historical text to explore different factors for the extraposition of relative clauses, demonstrating the practical value of computational approaches for linguistic studies. The developed methods are released as the CLASSIG pipeline (Computational Linguistic Analysis of Syntactic Structures In German) at https://github.com/rubcompling/classig- pipeline. Data sets, models, and evaluation results are provided for download at https://github.com/rubcompling/classig-data and https://doi.org/10.5281/zenodo.7180973.

• https://www.linguistics.rub.de/forschung/arbeitsberichte/25.pdf

@phdthesis{ortmann23,
title = {Computational Methods for Investigating Syntactic Change: Automatic Identification of Extraposition in Modern and Historical German},
author = {Katrin Ortmann},
url = {https://www.linguistics.rub.de/forschung/arbeitsberichte/25.pdf},
year = {2023},
date = {2023},
publisher = {Bochumer Linguistische Arbeitsberichte (BLA) 25},
abstract = {The linguistic analysis of historical German and diachronic syntactic change is traditionally based on small, manually annotated data sets. As a consequence, such studies lack the generalizability and statistical significance that quantitative approaches can offer. In this thesis, computational methods for the automatic syntactic analysis of modern and historical German are developed, which help to overcome the natural limits of manual annotation and enable the creation of large annotated data sets. The main goal of the thesis is to identify extraposition in modern and historical German, with extraposition being defined as the movement of constituents from their base position to the post-field of the sentence (H{\"o}hle 2019; W{\"o}llstein 2018). For the automatic recognition of extraposition, two annotation steps are combined: (i) a topological field analysis for the identification of post-fields and (ii) a constituency analysis to recognize candidates for extraposition. The thesis describes experiments on topological field parsing (Ortmann 2020), chunking (Ortmann 2021a), and constituency parsing (Ortmann 2021b). The best results are achieved with statistical models trained on Part-of-Speech tags as input. Contrary to previous studies, all annotation steps are thoroughly evaluated with the newly developed FairEval method for the fine-grained error analysis and fair evaluation of labeled spans (Ortmann 2022). In an example analysis, the created methods are applied to large collections of modern and historical text to explore different factors for the extraposition of relative clauses, demonstrating the practical value of computational approaches for linguistic studies. The developed methods are released as the CLASSIG pipeline (Computational Linguistic Analysis of Syntactic Structures In German) at https://github.com/rubcompling/classig- pipeline. Data sets, models, and evaluation results are provided for download at https://github.com/rubcompling/classig-data and https://doi.org/10.5281/zenodo.7180973.},
pubstate = {published},
type = {phdthesis}
}

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In noisy environments, speech can be hard to understand for humans. Spoken dialog systems can help to enhance the intelligibility of their output, either by modifying the speech synthesis (e.g., imitate Lombard speech) or by optimizing the language generation. We here focus on the second type of approach, by which an intended message is realized with words that are more intelligible in a specific noisy environment. By conducting a speech perception experiment, we created a dataset of 900 paraphrases in babble noise, perceived by native English speakers with normal hearing. We find that careful selection of paraphrases can improve intelligibility by 33% at SNR -5 dB. Our analysis of the data shows that the intelligibility differences between paraphrases are mainly driven by noise-robust acoustic cues. Furthermore, we propose an intelligibility-aware paraphrase ranking model, which outperforms baseline models with a relative improvement of 31.37% at SNR -5 dB.

• https://arxiv.org/abs/2210.10252
• https://doi.org/10.48550/arXiv.2210.10252

@inproceedings{Chingachametal23,
title = {A Data-Driven Investigation of Noise-Adaptive Utterance Generation with Linguistic Modification},
author = {Anupama Chingacham and Vera Demberg and Dietrich Klakow},
url = {https://arxiv.org/abs/2210.10252},
doi = {https://doi.org/10.48550/arXiv.2210.10252},
year = {2023},
date = {2023},
booktitle = {2022 IEEE Spoken Language Technology Workshop (SLT 2022, 9th - 12th January 2023, Doha, Qatar)},
abstract = {In noisy environments, speech can be hard to understand for humans. Spoken dialog systems can help to enhance the intelligibility of their output, either by modifying the speech synthesis (e.g., imitate Lombard speech) or by optimizing the language generation. We here focus on the second type of approach, by which an intended message is realized with words that are more intelligible in a specific noisy environment. By conducting a speech perception experiment, we created a dataset of 900 paraphrases in babble noise, perceived by native English speakers with normal hearing. We find that careful selection of paraphrases can improve intelligibility by 33% at SNR -5 dB. Our analysis of the data shows that the intelligibility differences between paraphrases are mainly driven by noise-robust acoustic cues. Furthermore, we propose an intelligibility-aware paraphrase ranking model, which outperforms baseline models with a relative improvement of 31.37% at SNR -5 dB.},
pubstate = {published},
type = {inproceedings}
}

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This paper focuses on the distinctive features of translated and interpreted texts in specific language combinations as forms of mediated discourse at the European Parliament. We aim to contribute to the long line of research on the specific properties of translation/interpreting. Specifically, we are interested in mediation effects (translation vs. interpreting) vs. effects of discourse mode (written vs. spoken). We propose a data-driven, exploratory approach to detecting and evaluating linguistic features as typical of translation/interpreting. Our approach utilizes simple wordbased 𝑛-gram language models combined with the information-theoretic measure of relative entropy, a standard measure of similarity/difference between probability distributions, applied here as a method of corpus comparison. Comparing translation
and interpreting (including the relation to their originals), we confirm the previously observed overall trend of written vs. spoken mode being strongly reflected in the translation and interpreting output. In addition, we detect some new features, such as a tendency towards more general lexemes in the verbal domain in interpreting or features of nominal style in translation.

• https://langsci-press.org/catalog/book/343
• https://doi.org/10.5281/zenodo.6977050

@inbook{Przybyl2021exploring,
title = {Exploring linguistic variation in mediated discourse: translation vs. interpreting},
author = {Heike Przybyl and Alina Karakanta and Katrin Menzel and Elke Teich},
editor = {Marta Kajzer-Wietrzny and Silvia Bernardini and Adriano Ferraresi and Ilmari Ivaska},
url = {https://langsci-press.org/catalog/book/343},
doi = {https://doi.org/10.5281/zenodo.6977050},
year = {2022},
date = {2022},
booktitle = {Mediated discourse at the European Parliament: Empirical investigations},
pages = {191–218},
publisher = {Language Science Press},
address = {Berlin},
abstract = {This paper focuses on the distinctive features of translated and interpreted texts in specific language combinations as forms of mediated discourse at the European Parliament. We aim to contribute to the long line of research on the specific properties of translation/interpreting. Specifically, we are interested in mediation effects (translation vs. interpreting) vs. effects of discourse mode (written vs. spoken). We propose a data-driven, exploratory approach to detecting and evaluating linguistic features as typical of translation/interpreting. Our approach utilizes simple wordbased 𝑛-gram language models combined with the information-theoretic measure of relative entropy, a standard measure of similarity/difference between probability distributions, applied here as a method of corpus comparison. Comparing translation and interpreting (including the relation to their originals), we confirm the previously observed overall trend of written vs. spoken mode being strongly reflected in the translation and interpreting output. In addition, we detect some new features, such as a tendency towards more general lexemes in the verbal domain in interpreting or features of nominal style in translation.},
pubstate = {published},
type = {inbook}
}

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Multilingual pre-trained language models (PLMs) have demonstrated impressive performance on several downstream tasks for both high-resourced and low-resourced languages. However, there is still a large performance drop for languages unseen during pre-training, especially African languages. One of the most effective approaches to adapt to a new language is language adaptive fine-tuning (LAFT) {—} fine-tuning a multilingual PLM on monolingual texts of a language using the pre-training objective. However, adapting to target language individually takes large disk space and limits the cross-lingual transfer abilities of the resulting models because they have been specialized for a single language. In this paper, we perform multilingual adaptive fine-tuning on 17 most-resourced African languages and three other high-resource languages widely spoken on the African continent to encourage cross-lingual transfer learning. To further specialize the multilingual PLM, we removed vocabulary tokens from the embedding layer that corresponds to non-African writing scripts before MAFT, thus reducing the model size by around 50{\%}. Our evaluation on two multilingual PLMs (AfriBERTa and XLM-R) and three NLP tasks (NER, news topic classification, and sentiment classification) shows that our approach is competitive to applying LAFT on individual languages while requiring significantly less disk space. Additionally, we show that our adapted PLM also improves the zero-shot cross-lingual transfer abilities of parameter efficient fine-tuning methods.

• https://aclanthology.org/2022.coling-1.382

@inproceedings{alabi-etal-2022-adapting,
title = {Adapting Pre-trained Language Models to African Languages via Multilingual Adaptive Fine-Tuning},
author = {Alabi Jesujoba and David Adelani and Marius Mosbach and Dietrich Klakow},
url = {https://aclanthology.org/2022.coling-1.382},
year = {2022},
date = {2022},
booktitle = {Proceedings of the 29th International Conference on Computational Linguistics},
pages = {4336-4349},
publisher = {International Committee on Computational Linguistics},
address = {Gyeongju, Republic of Korea},
abstract = {Multilingual pre-trained language models (PLMs) have demonstrated impressive performance on several downstream tasks for both high-resourced and low-resourced languages. However, there is still a large performance drop for languages unseen during pre-training, especially African languages. One of the most effective approaches to adapt to a new language is language adaptive fine-tuning (LAFT) {---} fine-tuning a multilingual PLM on monolingual texts of a language using the pre-training objective. However, adapting to target language individually takes large disk space and limits the cross-lingual transfer abilities of the resulting models because they have been specialized for a single language. In this paper, we perform multilingual adaptive fine-tuning on 17 most-resourced African languages and three other high-resource languages widely spoken on the African continent to encourage cross-lingual transfer learning. To further specialize the multilingual PLM, we removed vocabulary tokens from the embedding layer that corresponds to non-African writing scripts before MAFT, thus reducing the model size by around 50{\%}. Our evaluation on two multilingual PLMs (AfriBERTa and XLM-R) and three NLP tasks (NER, news topic classification, and sentiment classification) shows that our approach is competitive to applying LAFT on individual languages while requiring significantly less disk space. Additionally, we show that our adapted PLM also improves the zero-shot cross-lingual transfer abilities of parameter efficient fine-tuning methods.},
pubstate = {published},
type = {inproceedings}
}

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We present a study of discourse connectives in English-German and German-English translation and interpreting where we focus on the phenomena of explicitation and implicitation.
Apart from distributional analysis of translation patterns in parallel data, we also look into surprisal, i.e. an information-theoretic measure of cognitive effort, which helps us to interpret the observed tendencies.

• art-lapshinova-koltunski-pollklaesener-przybyl     (0.2MB)
• https://ufal.mff.cuni.cz/pbml/119/art-lapshinova-koltunski-pollklaesener-przybyl.pdf
• https://doi.org/10.14712/00326585.020

@article{lapshinova-koltunski-pollklaesener-przybyl:2022,
title = {Exploring Explicitation and Implicitation in Parallel Interpreting and Translation Corpora},
author = {Ekaterina Lapshinova-Koltunski and Christina Pollkl{\"a}sener and Heike Przybyl},
url = {https://ufal.mff.cuni.cz/pbml/119/art-lapshinova-koltunski-pollklaesener-przybyl.pdf},
doi = {https://doi.org/10.14712/00326585.020},
year = {2022},
date = {2022},
journal = {The Prague Bulletin of Mathematical Linguistics},
pages = {5-22},
volume = {119},
abstract = {We present a study of discourse connectives in English-German and German-English translation and interpreting where we focus on the phenomena of explicitation and implicitation. Apart from distributional analysis of translation patterns in parallel data, we also look into surprisal, i.e. an information-theoretic measure of cognitive effort, which helps us to interpret the observed tendencies.},
pubstate = {published},
type = {article}
}

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This work presents the results of an auditory language of origin identification experiment. Disyllabic and trisyllabic logatomes were recorded by speakers of Bulgarian, Czech, Polish, and Russian, and presented to L1 speakers of the abovementioned Slavic languages. The goals of the test were to verify the ability of lay listeners to recognize the linguistic origin of speakers, based on spoken samples with limited segmental and suprasegmental information, and to correlate the signal features with the subjects’ performance. It was found that position of word stress is not an important predictor in language recognition. However, inherent vowel characteristics such as duration and vowel space computed by the means of Pillai scores correlate with subjects’ performance. Both the linguistic profile and the familiarity with closely related languages also appear to be relevant predictors of listeners’ performance. Finally, the information-theoretic notion of surprisal applied on regular cross-linguistic sound correspondences was correlated with recognition scores; though, the correlations did not reach the threshold of statistical significance. We conclude that auditory identification of linguistic origin by lay persons, native speakers of closely related languages, is possible even when exposed to limited segmental information, which can serve as a cue in the identification of linguistic origin.

• https://journals.sagepub.com/eprint/JJIKHP9RPEYZM2EQKFWZ/full
• https://doi.org/10.1177/00238309221119098

@article{kudera_etal2022_cues,
title = {Phonetic cues in auditory identification of Bulgarian, Czech, Polish, and Russian language of origin},
author = {Jacek Kudera and Irina Stenger and Bernd M{\"o}bius and Tania Avgustinova and Dietrich Klakow},
url = {https://journals.sagepub.com/eprint/JJIKHP9RPEYZM2EQKFWZ/full},
doi = {https://doi.org/10.1177/00238309221119098},
year = {2022},
date = {2022-09-01},
journal = {Language and Speech},
abstract = {This work presents the results of an auditory language of origin identification experiment. Disyllabic and trisyllabic logatomes were recorded by speakers of Bulgarian, Czech, Polish, and Russian, and presented to L1 speakers of the abovementioned Slavic languages. The goals of the test were to verify the ability of lay listeners to recognize the linguistic origin of speakers, based on spoken samples with limited segmental and suprasegmental information, and to correlate the signal features with the subjects’ performance. It was found that position of word stress is not an important predictor in language recognition. However, inherent vowel characteristics such as duration and vowel space computed by the means of Pillai scores correlate with subjects’ performance. Both the linguistic profile and the familiarity with closely related languages also appear to be relevant predictors of listeners’ performance. Finally, the information-theoretic notion of surprisal applied on regular cross-linguistic sound correspondences was correlated with recognition scores; though, the correlations did not reach the threshold of statistical significance. We conclude that auditory identification of linguistic origin by lay persons, native speakers of closely related languages, is possible even when exposed to limited segmental information, which can serve as a cue in the identification of linguistic origin.},
pubstate = {published},
type = {article}
}

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Learning semantically meaningful sentence embeddings is an open problem in natural language processing. In this work, we propose a sentence embedding learning approach that exploits both visual and textual information via a multimodal contrastive objective. Through experiments on a variety of semantic textual similarity tasks, we demonstrate that our approach consistently improves the performance across various datasets and pre-trained encoders. In particular, combining a small amount of multimodal data with a large text-only corpus, we improve the state-of-the-art average Spearman{‚}s correlation by 1.7{\%}. By analyzing the properties of the textual embedding space, we show that our model excels in aligning semantically similar sentences, providing an explanation for its improved performance.

• 2022.naacl-main.436     (1.82MB)
• https://aclanthology.org/2022.naacl-main.436
• https://doi.org/10.18653/v1/2022.naacl-main.436

@inproceedings{zhang-etal-2022-mcse,
title = {MCSE: Multimodal Contrastive Learning of Sentence Embeddings},
author = {Miaoran Zhang and Marius Mosbach and David Adelani and Michael Hedderich and Dietrich Klakow},
url = {https://aclanthology.org/2022.naacl-main.436},
doi = {https://doi.org/10.18653/v1/2022.naacl-main.436},
year = {2022},
date = {2022},
booktitle = {Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
pages = {5959-5969},
publisher = {Association for Computational Linguistics},
address = {Seattle, United States},
abstract = {Learning semantically meaningful sentence embeddings is an open problem in natural language processing. In this work, we propose a sentence embedding learning approach that exploits both visual and textual information via a multimodal contrastive objective. Through experiments on a variety of semantic textual similarity tasks, we demonstrate that our approach consistently improves the performance across various datasets and pre-trained encoders. In particular, combining a small amount of multimodal data with a large text-only corpus, we improve the state-of-the-art average Spearman{'}s correlation by 1.7{\%}. By analyzing the properties of the textual embedding space, we show that our model excels in aligning semantically similar sentences, providing an explanation for its improved performance.},
pubstate = {published},
type = {inproceedings}
}

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Acoustic word embeddings (AWEs) are fixed-dimensionality vector representations in a vector space such that different acoustic exemplars of the same word are projected nearby in the embedding space. In addition to their use in speech technology applications such as spoken term discovery and keyword spotting, AWE models have been adopted as models of spoken-word processing in several cognitively motivated studies and they have shown to exhibit a human-like performance in some auditory processing tasks. Nevertheless, the representation geometry of AWEs remains an under-explored topic that has not been studied in the literature. In this paper, we take a closer analytical look at AWEs and study how the choice of the learning objective and the architecture shapes their representational profile. Our main findings highlight the prominent role of the learning objective on the representational geometry over the architecture.

• 2022.blackboxnlp-1.15     (1.19MB)
• https://aclanthology.org/2022.blackboxnlp-1.15
• https://doi.org/10.18653/v1/2022.blackboxnlp-1.15

@inproceedings{abdullah-klakow-2022-analyzing,
title = {Analyzing the Representational Geometry of Acoustic Word Embeddings},
author = {Badr M. Abdullah and Dietrich Klakow},
url = {https://aclanthology.org/2022.blackboxnlp-1.15},
doi = {https://doi.org/10.18653/v1/2022.blackboxnlp-1.15},
year = {2022},
date = {2022},
booktitle = {Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP},
pages = {178-191},
publisher = {Association for Computational Linguistics},
address = {Abu Dhabi, United Arab Emirates (Hybrid)},
abstract = {Acoustic word embeddings (AWEs) are fixed-dimensionality vector representations in a vector space such that different acoustic exemplars of the same word are projected nearby in the embedding space. In addition to their use in speech technology applications such as spoken term discovery and keyword spotting, AWE models have been adopted as models of spoken-word processing in several cognitively motivated studies and they have shown to exhibit a human-like performance in some auditory processing tasks. Nevertheless, the representation geometry of AWEs remains an under-explored topic that has not been studied in the literature. In this paper, we take a closer analytical look at AWEs and study how the choice of the learning objective and the architecture shapes their representational profile. Our main findings highlight the prominent role of the learning objective on the representational geometry over the architecture.},
pubstate = {published},
type = {inproceedings}
}

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Speakers tend to speak clearly in noisy environments, while they tend to reserve effort by shortening word duration in predictable contexts. It is unclear how these two communicative demands are met. The current study investigates the acoustic realizations of syllables in predictable vs unpredictable contexts across different background noise levels. Thirty-eight German native speakers produced 60 CV syllables in two predictability contexts in three noise conditions (reference = quiet, 0 dB and −10 dB signal-to-noise ratio). Duration, intensity (average and range), F0 (median), and vowel formants of the target syllables were analysed. The presence of noise yielded significantly longer duration, higher average intensity, larger intensity range, and higher F0. Noise levels affected intensity (average and range) and F0. Low predictability syllables exhibited longer duration and larger intensity range. However, no interaction was found between noise and predictability. This suggests that noise-related modifications might be independent of predictability-related changes, with implications for including channel-based and message-based formulations in speech production.

• ibrahim_etal_jasa2022     (1.49MB)
• https://asa.scitation.org/doi/10.1121/10.0013413
• https://doi.org/10.1121/10.0013413

@article{ibrahim_etal_jasa2022,
title = {The combined effects of contextual predictability and noise on the acoustic realisation of German syllables},
author = {Omnia Ibrahim and Ivan Yuen and Marjolein van Os and Bistra Andreeva and Bernd M{\"o}bius},
url = {https://asa.scitation.org/doi/10.1121/10.0013413},
doi = {https://doi.org/10.1121/10.0013413},
year = {2022},
date = {2022-08-10},
journal = {The Journal of the Acoustical Society of America},
volume = {152},
number = {2},
abstract = {Speakers tend to speak clearly in noisy environments, while they tend to reserve effort by shortening word duration in predictable contexts. It is unclear how these two communicative demands are met. The current study investigates the acoustic realizations of syllables in predictable vs unpredictable contexts across different background noise levels. Thirty-eight German native speakers produced 60 CV syllables in two predictability contexts in three noise conditions (reference = quiet, 0 dB and −10 dB signal-to-noise ratio). Duration, intensity (average and range), F0 (median), and vowel formants of the target syllables were analysed. The presence of noise yielded significantly longer duration, higher average intensity, larger intensity range, and higher F0. Noise levels affected intensity (average and range) and F0. Low predictability syllables exhibited longer duration and larger intensity range. However, no interaction was found between noise and predictability. This suggests that noise-related modifications might be independent of predictability-related changes, with implications for including channel-based and message-based formulations in speech production.},
pubstate = {published},
type = {article}
}

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The aim of this study was to examine the role of attention in understanding linguistic information even in a noisy environment. To assess the role of attention, we varied task instructions in two experiments in which participants were instructed to listen to short sentences and thereafter to type in the last word they heard or to type in the whole sentence. We were interested in how these task instructions influence the interplay between top-down prediction and bottom-up perceptual processes during language comprehension. Therefore, we created sentences that varied in the degree of predictability (low, medium, and high) as well as in the degree of speech degradation (four, six, and eight noise-vocoding channels). Results indicated better word recognition for highly predictable sentences for moderate, though not for high, levels of speech degradation, but only when attention was directed to the whole sentence. This underlines the important role of attention in language comprehension.

• https://www.cambridge.org/core/journals/language-and-cognition/article/abs/predictability-effects-in-degraded-speech-comprehension-are-reduced-as-a-function-of-attention/98F4E3A4A3FC0B7E00C8E1536D986853
• https://doi.org/10.1017/langcog.2022.16

@article{bhandari_demberg_kray_2022,
title = {Predictability effects in degraded speech comprehension are reduced as a function of attention},
author = {Pratik Bhandari and Vera Demberg and Jutta Kray},
url = {https://www.cambridge.org/core/journals/language-and-cognition/article/abs/predictability-effects-in-degraded-speech-comprehension-are-reduced-as-a-function-of-attention/98F4E3A4A3FC0B7E00C8E1536D986853},
doi = {https://doi.org/10.1017/langcog.2022.16},
year = {2022},
date = {2022-07-22},
journal = {Language and Cognition},
pages = {1-18},
publisher = {Cambridge University Press},
abstract = {The aim of this study was to examine the role of attention in understanding linguistic information even in a noisy environment. To assess the role of attention, we varied task instructions in two experiments in which participants were instructed to listen to short sentences and thereafter to type in the last word they heard or to type in the whole sentence. We were interested in how these task instructions influence the interplay between top-down prediction and bottom-up perceptual processes during language comprehension. Therefore, we created sentences that varied in the degree of predictability (low, medium, and high) as well as in the degree of speech degradation (four, six, and eight noise-vocoding channels). Results indicated better word recognition for highly predictable sentences for moderate, though not for high, levels of speech degradation, but only when attention was directed to the whole sentence. This underlines the important role of attention in language comprehension.},
pubstate = {published},
type = {article}
}

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In this paper, we describe the creation and annotation of EPIC UdS, a multilingual corpus of simultaneous interpreting for English, German and Spanish. We give an overview of the comparable and parallel, aligned corpus variants and explore various applications of the corpus. What makes EPIC UdS relevant is that it is one of the rare interpreting corpora that includes transcripts suitable for research on more than one language pair and on interpreting with regard to German. It not only contains transcribed speeches, but also rich metadata and fine-grained linguistic annotations tailored for diverse applications across a broad range of linguistic subfields.

• https://aclanthology.org/2022.lrec-1.127/

@inproceedings{Przybyl_interpreting_2022,
title = {EPIC UdS - Creation and applications of a simultaneous interpreting corpus},
author = {Heike Przybyl and Ekaterina Lapshinova-Koltunski and Katrin Menzel and Stefan Fischer and Elke Teich},
url = {https://aclanthology.org/2022.lrec-1.127/},
year = {2022},
date = {2022},
booktitle = {Proceedings of the  13th Conference on Language Resources and Evaluation (LREC 2022)},
pages = {1193–1200},
address = {Marseille, France, 20-25 June 2022},
abstract = {In this paper, we describe the creation and annotation of EPIC UdS, a multilingual corpus of simultaneous interpreting for English, German and Spanish. We give an overview of the comparable and parallel, aligned corpus variants and explore various applications of the corpus. What makes EPIC UdS relevant is that it is one of the rare interpreting corpora that includes transcripts suitable for research on more than one language pair and on interpreting with regard to German. It not only contains transcribed speeches, but also rich metadata and fine-grained linguistic annotations tailored for diverse applications across a broad range of linguistic subfields.},
pubstate = {published},
type = {inproceedings}
}

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