TY - GEN A1 - Offrede, Tom F. A1 - Jacobi, Jidde A1 - Rebernik, Teja A1 - de Jong, Lisanne A1 - Keulen, Stefanie A1 - Veenstra, Pauline A1 - Noiray, Aude A1 - Wieling, Martijn T1 - The impact of alcohol on L1 versus L2 T2 - Zweitveröffentlichungen der Universität Potsdam : Humanwissenschaftliche Reihe N2 - Alcohol intoxication is known to affect many aspects of human behavior and cognition; one of such affected systems is articulation during speech production. Although much research has revealed that alcohol negatively impacts pronunciation in a first language (L1), there is only initial evidence suggesting a potential beneficial effect of inebriation on articulation in a non-native language (L2). The aim of this study was thus to compare the effect of alcohol consumption on pronunciation in an L1 and an L2. Participants who had ingested different amounts of alcohol provided speech samples in their L1 (Dutch) and L2 (English), and native speakers of each language subsequently rated the pronunciation of these samples on their intelligibility (for the L1) and accent nativelikeness (for the L2). These data were analyzed with generalized additive mixed modeling. Participants' blood alcohol concentration indeed negatively affected pronunciation in L1, but it produced no significant effect on the L2 accent ratings. The expected negative impact of alcohol on L1 articulation can be explained by reduction in fine motor control. We present two hypotheses to account for the absence of any effects of intoxication on L2 pronunciation: (1) there may be a reduction in L1 interference on L2 speech due to decreased motor control or (2) alcohol may produce a differential effect on each of the two linguistic subsystems. T3 - Zweitveröffentlichungen der Universität Potsdam : Humanwissenschaftliche Reihe - 848 KW - acute alcohol consumption KW - articulation KW - speech KW - bilingualism Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-540955 SN - 1866-8364 IS - 3 ER - TY - JOUR A1 - Offrede, Tom F. A1 - Jacobi, Jidde A1 - Rebernik, Teja A1 - de Jong, Lisanne A1 - Keulen, Stefanie A1 - Veenstra, Pauline A1 - Noiray, Aude A1 - Wieling, Martijn T1 - The impact of alcohol on L1 versus L2 JF - Language and Speech N2 - Alcohol intoxication is known to affect many aspects of human behavior and cognition; one of such affected systems is articulation during speech production. Although much research has revealed that alcohol negatively impacts pronunciation in a first language (L1), there is only initial evidence suggesting a potential beneficial effect of inebriation on articulation in a non-native language (L2). The aim of this study was thus to compare the effect of alcohol consumption on pronunciation in an L1 and an L2. Participants who had ingested different amounts of alcohol provided speech samples in their L1 (Dutch) and L2 (English), and native speakers of each language subsequently rated the pronunciation of these samples on their intelligibility (for the L1) and accent nativelikeness (for the L2). These data were analyzed with generalized additive mixed modeling. Participants' blood alcohol concentration indeed negatively affected pronunciation in L1, but it produced no significant effect on the L2 accent ratings. The expected negative impact of alcohol on L1 articulation can be explained by reduction in fine motor control. We present two hypotheses to account for the absence of any effects of intoxication on L2 pronunciation: (1) there may be a reduction in L1 interference on L2 speech due to decreased motor control or (2) alcohol may produce a differential effect on each of the two linguistic subsystems. KW - acute alcohol consumption KW - articulation KW - speech KW - bilingualism Y1 - 2020 U6 - https://doi.org/10.1177/0023830920953169 SN - 1756-6053 SN - 0023-8309 VL - 64 IS - 3 SP - 681 EP - 692 PB - SAGE Publications CY - Thousand Oaks ER - TY - THES A1 - López Gambino, Maria Soledad T1 - Time Buying in Task-Oriented Spoken Dialogue Systems N2 - This dissertation focuses on the handling of time in dialogue. Specifically, it investigates how humans bridge time, or “buy time”, when they are expected to convey information that is not yet available to them (e.g. a travel agent searching for a flight in a long list while the customer is on the line, waiting). It also explores the feasibility of modeling such time-bridging behavior in spoken dialogue systems, and it examines how endowing such systems with more human-like time-bridging capabilities may affect humans’ perception of them. The relevance of time-bridging in human-human dialogue seems to stem largely from a need to avoid lengthy pauses, as these may cause both confusion and discomfort among the participants of a conversation (Levinson, 1983; Lundholm Fors, 2015). However, this avoidance of prolonged silence is at odds with the incremental nature of speech production in dialogue (Schlangen and Skantze, 2011): Speakers often start to verbalize their contribution before it is fully formulated, and sometimes even before they possess the information they need to provide, which may result in them running out of content mid-turn. In this work, we elicit conversational data from humans, to learn how they avoid being silent while they search for information to convey to their interlocutor. We identify commonalities in the types of resources employed by different speakers, and we propose a classification scheme. We explore ways of modeling human time-buying behavior computationally, and we evaluate the effect on human listeners of embedding this behavior in a spoken dialogue system. Our results suggest that a system using conversational speech to bridge time while searching for information to convey (as humans do) can provide a better experience in several respects than one which remains silent for a long period of time. However, not all speech serves this purpose equally: Our experiments also show that a system whose time-buying behavior is more varied (i.e. which exploits several categories from the classification scheme we developed and samples them based on information from human data) can prevent overestimation of waiting time when compared, for example, with a system that repeatedly asks the interlocutor to wait (even if these requests for waiting are phrased differently each time). Finally, this research shows that it is possible to model human time-buying behavior on a relatively small corpus, and that a system using such a model can be preferred by participants over one employing a simpler strategy, such as randomly choosing utterances to produce during the wait —even when the utterances used by both strategies are the same. N2 - Die zentralen Themen dieser Arbeit sind Zeit und Dialog. Insbesondere wird untersucht, wie Menschen Zeit gewinnen oder „Zeit kaufen“, wenn sie Informationen übermitteln müssen, die ihnen noch nicht zur Verfügung stehen (z. B. ein Reisebüroangestellter, der in einer langen Liste nach einem Flug sucht, während der Kunde am Telefon wartet). Außerdem wird untersucht, ob die Modellierung eines solchen Zeitüberbrückungsverhaltens in gesprochenen Dialogsystemen möglich ist und wie solche Fähigkeiten die Benutzererfahrung beeinflussen. Wir erheben Gesprächsdaten und ermitteln, wie die Sprecher den Dialog am Laufen halten, während sie nach Informationen für ihre(n) Gesprächspartner(in) suchen. Wir identifizieren Gemeinsamkeiten in den Ressourcen, die von verschiedenen Sprechern verwendet werden und schlagen ein Klassifizierungsschema vor. Wir erforschen Strategien, menschliches „Zeitüberbrückung“ zu modellieren, und wir bewerten die Auswirkungen dieses Verhaltens in ein gesprochenes Dialogsystem auf menschliche Zuhörer. T2 - Zeitgewinn in aufgabenorientierten Sprachdialogsystemen KW - dialogue system KW - Dialogsystem KW - linguistics KW - Linguistik KW - speech KW - Sprache KW - dialogue KW - Dialog KW - time-buying KW - Zeitgewinn Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-592806 ER - TY - JOUR A1 - Gafos, Adamantios I. A1 - Lieshout, Pascal H. H. M. van T1 - Models and theories of speech production BT - editorial JF - Frontiers in psychology KW - speech production KW - motor control KW - dynamical models KW - phonology KW - speech KW - disorders KW - timing Y1 - 2020 U6 - https://doi.org/10.3389/fpsyg.2020.01238 SN - 1664-1078 VL - 11 PB - Frontiers Research Foundation CY - Lausanne ER - TY - JOUR A1 - Hecker, Pascal A1 - Steckhan, Nico A1 - Eyben, Florian A1 - Schuller, Björn Wolfgang A1 - Arnrich, Bert T1 - Voice Analysis for Neurological Disorder Recognition – A Systematic Review and Perspective on Emerging Trends JF - Frontiers in Digital Health N2 - Quantifying neurological disorders from voice is a rapidly growing field of research and holds promise for unobtrusive and large-scale disorder monitoring. The data recording setup and data analysis pipelines are both crucial aspects to effectively obtain relevant information from participants. Therefore, we performed a systematic review to provide a high-level overview of practices across various neurological disorders and highlight emerging trends. PRISMA-based literature searches were conducted through PubMed, Web of Science, and IEEE Xplore to identify publications in which original (i.e., newly recorded) datasets were collected. Disorders of interest were psychiatric as well as neurodegenerative disorders, such as bipolar disorder, depression, and stress, as well as amyotrophic lateral sclerosis amyotrophic lateral sclerosis, Alzheimer's, and Parkinson's disease, and speech impairments (aphasia, dysarthria, and dysphonia). Of the 43 retrieved studies, Parkinson's disease is represented most prominently with 19 discovered datasets. Free speech and read speech tasks are most commonly used across disorders. Besides popular feature extraction toolkits, many studies utilise custom-built feature sets. Correlations of acoustic features with psychiatric and neurodegenerative disorders are presented. In terms of analysis, statistical analysis for significance of individual features is commonly used, as well as predictive modeling approaches, especially with support vector machines and a small number of artificial neural networks. An emerging trend and recommendation for future studies is to collect data in everyday life to facilitate longitudinal data collection and to capture the behavior of participants more naturally. Another emerging trend is to record additional modalities to voice, which can potentially increase analytical performance. KW - neurological disorders KW - voice KW - speech KW - everyday life KW - multiple modalities KW - machine learning KW - disorder recognition Y1 - 2022 U6 - https://doi.org/10.3389/fdgth.2022.842301 SN - 2673-253X PB - Frontiers Media SA CY - Lausanne, Schweiz ER - TY - GEN A1 - Hecker, Pascal A1 - Steckhan, Nico A1 - Eyben, Florian A1 - Schuller, Björn Wolfgang A1 - Arnrich, Bert T1 - Voice Analysis for Neurological Disorder Recognition – A Systematic Review and Perspective on Emerging Trends T2 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät N2 - Quantifying neurological disorders from voice is a rapidly growing field of research and holds promise for unobtrusive and large-scale disorder monitoring. The data recording setup and data analysis pipelines are both crucial aspects to effectively obtain relevant information from participants. Therefore, we performed a systematic review to provide a high-level overview of practices across various neurological disorders and highlight emerging trends. PRISMA-based literature searches were conducted through PubMed, Web of Science, and IEEE Xplore to identify publications in which original (i.e., newly recorded) datasets were collected. Disorders of interest were psychiatric as well as neurodegenerative disorders, such as bipolar disorder, depression, and stress, as well as amyotrophic lateral sclerosis amyotrophic lateral sclerosis, Alzheimer's, and Parkinson's disease, and speech impairments (aphasia, dysarthria, and dysphonia). Of the 43 retrieved studies, Parkinson's disease is represented most prominently with 19 discovered datasets. Free speech and read speech tasks are most commonly used across disorders. Besides popular feature extraction toolkits, many studies utilise custom-built feature sets. Correlations of acoustic features with psychiatric and neurodegenerative disorders are presented. In terms of analysis, statistical analysis for significance of individual features is commonly used, as well as predictive modeling approaches, especially with support vector machines and a small number of artificial neural networks. An emerging trend and recommendation for future studies is to collect data in everyday life to facilitate longitudinal data collection and to capture the behavior of participants more naturally. Another emerging trend is to record additional modalities to voice, which can potentially increase analytical performance. T3 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 13 KW - neurological disorders KW - voice KW - speech KW - everyday life KW - multiple modalities KW - machine learning KW - disorder recognition Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-581019 IS - 13 ER - TY - JOUR A1 - Mokari, Payam Ghaffarvand A1 - Gafos, Adamantios I. A1 - Williams, Daniel T1 - Perceptuomotor compatibility effects in vowels BT - effects of consonantal context and acoustic proximity of response and distractor JF - JASA Express Letters N2 - In a cue-distractor task, speakers' response times (RTs) were found to speed up when they perceived a distractor syllable whose vowel was identical to the vowel in the syllable they were preparing to utter. At a more fine-grained level, subphonemic congruency between response and distractor-defined by higher number of shared phonological features or higher acoustic proximity-was also found to be predictive of RT modulations. Furthermore, the findings indicate that perception of vowel stimuli embedded in syllables gives rise to robust and more consistent perceptuomotor compatibility effects (compared to isolated vowels) across different response-distractor vowel pairs. KW - speech Y1 - 2021 U6 - https://doi.org/10.1121/10.0003039 SN - 2691-1191 VL - 1 IS - 1 PB - American Institute of Physics CY - Melville ER - TY - JOUR A1 - Boll-Avetisyan, Natalie A1 - Bhatara, Anjali A1 - Höhle, Barbara T1 - Effects of musicality on the perception of rhythmic structure in speech JF - Laboratory phonology N2 - Language and music share many rhythmic properties, such as variations in intensity and duration leading to repeating patterns. Perception of rhythmic properties may rely on cognitive networks that are shared between the two domains. If so, then variability in speech rhythm perception may relate to individual differences in musicality. To examine this possibility, the present study focuses on rhythmic grouping, which is assumed to be guided by a domain-general principle, the Iambic/Trochaic law, stating that sounds alternating in intensity are grouped as strong-weak, and sounds alternating in duration are grouped as weak-strong. German listeners completed a grouping task: They heard streams of syllables alternating in intensity, duration, or neither, and had to indicate whether they perceived a strong-weak or weak-strong pattern. Moreover, their music perception abilities were measured, and they filled out a questionnaire reporting their productive musical experience. Results showed that better musical rhythm perception - ability was associated with more consistent rhythmic grouping of speech, while melody perception - ability and productive musical experience were not. This suggests shared cognitive procedures in the perception of rhythm in music and speech. Also, the results highlight the relevance of - considering individual differences in musicality when aiming to explain variability in prosody perception. KW - Musical ability KW - rhythm KW - grouping KW - Iambic/Trochaic law KW - speech KW - speech perception KW - musicality KW - prosody KW - domain-general KW - German Y1 - 2017 U6 - https://doi.org/10.5334/labphon.91 SN - 1868-6346 SN - 1868-6354 VL - 8 IS - 1 PB - Ubiquity Press CY - London ER - TY - GEN A1 - Ott, Susan A1 - Höhle, Barbara T1 - Verb inflection in German-learning children with typical and atypical language acquisition BT - the impact of subsyllabic frequencies T2 - Journal of Child Language N2 - Previous research has shown that high phonotactic frequencies facilitate the production of regularly inflected verbs in English-learning children with specific language impairment (SLI) but not with typical development (TD). We asked whether this finding can be replicated for German, a language with a much more complex inflectional verb paradigm than English. Using an elicitation task, the production of inflected nonce verb forms (3 rd person singular with -t suffix) with either high- or low-frequency subsyllables was tested in sixteen German-learning children with SLI (ages 4;1–5 ;1), sixteen TD-children matched for chronological age (CA) and fourteen TD- children matched for verbal age (VA) (ages 3;0–3 ;11). The findings revealed that children with SLI, but not CA- or VA-children, showed differential performance between the two types of verbs, producing more inflectional errors when the verb forms resulted in low-frequency subsyllables than when they resulted in high-frequency subsyllables, replicating the results from English-learning children. T3 - Zweitveröffentlichungen der Universität Potsdam : Humanwissenschaftliche Reihe - 530 KW - english past tense KW - phonotactic probability KW - sentence repetition KW - nonword repetition KW - speaking children KW - impairment KW - morphology KW - infants KW - speech KW - words Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-416475 SN - 1866-8364 IS - 530 ER - TY - GEN A1 - Shaw, Jason A. A1 - Gafos, Adamantios I. A1 - Hoole, Philip A1 - Zeroual, Chakir T1 - Dynamic invariance in the phonetic expression of syllable structure BT - a case study of Moroccan Arabic consonant clusters T2 - Postprints der Universität Potsdam : Humanwissenschaftliche Reihe N2 - We asked whether invariant phonetic indices for syllable structure can be identified in a language where word-initial consonant clusters, regardless of their sonority profile, are claimed to be parsed heterosyllabically. Four speakers of Moroccan Arabic were recorded, using Electromagnetic Articulography. Pursuing previous work, we employed temporal diagnostics for syllable structure, consisting of static correspondences between any given phonological organisation and its presumed phonetic indices. We show that such correspondences offer only a partial understanding of the relation between syllabic organisation and continuous indices of that organisation. We analyse the failure of the diagnostics and put forth a new approach in which different phonological organisations prescribe different ways in which phonetic indices change as phonetic parameters are scaled. The main finding is that invariance is found in these patterns of change, rather than in static correspondences between phonological constructs and fixed values for their phonetic indices. T3 - Zweitveröffentlichungen der Universität Potsdam : Humanwissenschaftliche Reihe - 516 KW - american english KW - perception KW - speech KW - organization KW - duration KW - patterns KW - syllabication KW - articulation KW - sequences KW - knowledge Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-412479 SN - 1866-8364 IS - 516 SP - 455 EP - 490 ER -