Christina Bergmann

Publications

Displaying 1 - 24 of 24
  • Byers-Heinlein, K., Bergmann, C., Davies, C., Frank, M., Hamlin, J. K., Kline, M., Kominsky, J., Kosie, J., Lew-Williams, C., Liu, L., Mastroberardino, M., Singh, L., Waddell, C. P. G., Zettersten, M., & Soderstrom, M. (in press). Building a collaborative Psychological Science: Lessons learned from ManyBabies 1. Canadian Psychology/Psychologie canadienne.

    Abstract

    The field of infancy research faces a difficult challenge: some questions require samples that are simply too large for any one lab to recruit and test. ManyBabies aims to address this problem by forming large-scale collaborations on key theoretical questions in developmental science, while promoting the uptake of Open Science practices. Here, we look back on the first project completed under the ManyBabies umbrella – ManyBabies 1 – which tested the development of infant-directed speech preference. Our goal is to share the lessons learned over the course of the project and to articulate our vision for the role of large-scale collaborations in the field. First, we consider the decisions made in scaling up experimental research for a collaboration involving 100+ researchers and 70+ labs. Next, we discuss successes and challenges over the course of the project, including: protocol design and implementation, data analysis, organizational structures and collaborative workflows, securing funding, and encouraging broad participation in the project. Finally, we discuss the benefits we see both in ongoing ManyBabies projects and in future large-scale collaborations in general, with a particular eye towards developing best practices and increasing growth and diversity in infancy research and psychological science in general. Throughout the paper, we include first-hand narrative experiences, in order to illustrate the perspectives of researchers playing different roles within the project. While this project focused on the unique challenges of infant research, many of the insights we gained can be applied to large-scale collaborations across the broader field of psychology.
  • The ManyBabies Consortium (in press). Quantifying sources of variability in infancy research using the infant-directed speech preference. Advances in Methods and Practices in Psychological Science.
  • Tsuji, S., Cristia, A., Frank, M. C., & Bergmann, C. (in press). Addressing publication bias in meta-analysis: Empirical findings from community-augmented meta-analyses of infant language development. Zeitschrift für Psychologie.
  • Bergmann, C., Tsuji, S., Piccinini, P. E., Lewis, M. L., Braginsky, M. B., Frank, M. C., & Cristia, A. (2018). Promoting replicability in developmental research through meta-analyses: Insights from language acquisition research. Child Development, 89(6), 1996-2009. doi:10.1111/cdev.13079.

    Abstract

    Previous work suggests key factors for replicability, a necessary feature for theory building, include statistical power and appropriate research planning. These factors are examined by analyzing a collection of 12 standardized meta-analyses on language development between birth and 5 years. With a median effect size of Cohen's d= 0.45 and typical sample size of 18 participants, most research is underpowered (range: 6%-99%; median 44%); and calculating power based on seminal publications is not a suitable strategy. Method choice can be improved, as shown in analyses on exclusion rates and effect size as a function of method. The article ends with a discussion on how to increase replicability in both language acquisition studies specifically and developmental research more generally.
  • Bergmann, C., & Cristia, A. (2018). Environmental influences on infants’ native vowel discrimination: The case of talker number in daily life. Infancy, 23(4), 484-501. doi:10.1111/infa.12232.

    Abstract

    Both quality and quantity of speech from the primary caregiver have been found to impact language development. A third aspect of the input has been largely ignored: the number of talkers who provide input. Some infants spend most of their waking time with only one person; others hear many different talkers. Even if the very same words are spoken the same number of times, the pronunciations can be more variable when several talkers pronounce them. Is language acquisition affected by the number of people who provide input? To shed light on the possible link between how many people provide input in daily life and infants’ native vowel discrimination, three age groups were tested: 4-month-olds (before attunement to native vowels), 6-month-olds (at the cusp of native vowel attunement) and 12-month-olds (well attuned to the native vowel system). No relationship was found between talker number and native vowel discrimination skills in 4- and 6-month-olds, who are overall able to discriminate the vowel contrast. At 12 months, we observe a small positive relationship, but further analyses reveal that the data are also compatible with the null hypothesis of no relationship. Implications in the context of infant language acquisition and cognitive development are discussed.
  • Von Holzen, K., & Bergmann, C. (2018). A Meta-Analysis of Infants’ Mispronunciation Sensitivity Development. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 1159-1164). Austin, TX: Cognitive Science Society.

    Abstract

    Before infants become mature speakers of their native language, they must acquire a robust word-recognition system which allows them to strike the balance between allowing some variation (mood, voice, accent) and recognizing variability that potentially changes meaning (e.g. cat vs hat). The current meta-analysis quantifies how the latter, termed mispronunciation sensitivity, changes over infants’ first three years, testing competing predictions of mainstream language acquisition theories. Our results show that infants were sensitive to mispronunciations, but accepted them as labels for target objects. Interestingly, and in contrast to predictions of mainstream theories, mispronunciation sensitivity was not modulated by infant age, suggesting that a sufficiently flexible understanding of native language phonology is in place at a young age.
  • Bergmann, C., Tsuji, S., & Cristia, A. (2017). Top-down versus bottom-up theories of phonological acquisition: A big data approach. In Proceedings of Interspeech 2017 (pp. 2103-2107).

    Abstract

    Recent work has made available a number of standardized meta- analyses bearing on various aspects of infant language processing. We utilize data from two such meta-analyses (discrimination of vowel contrasts and word segmentation, i.e., recognition of word forms extracted from running speech) to assess whether the published body of empirical evidence supports a bottom-up versus a top-down theory of early phonological development by leveling the power of results from thousands of infants. We predicted that if infants can rely purely on auditory experience to develop their phonological categories, then vowel discrimination and word segmentation should develop in parallel, with the latter being potentially lagged compared to the former. However, if infants crucially rely on word form information to build their phonological categories, then development at the word level must precede the acquisition of native sound categories. Our results do not support the latter prediction. We discuss potential implications and limitations, most saliently that word forms are only one top-down level proposed to affect phonological development, with other proposals suggesting that top-down pressures emerge from lexical (i.e., word-meaning pairs) development. This investigation also highlights general procedures by which standardized meta-analyses may be reused to answer theoretical questions spanning across phenomena.

    Supplementary material

    Scripts and data
  • Black, A., & Bergmann, C. (2017). Quantifying infants' statistical word segmentation: A meta-analysis. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Meeting of the Cognitive Science Society (pp. 124-129). Austin, TX: Cognitive Science Society.

    Abstract

    Theories of language acquisition and perceptual learning increasingly rely on statistical learning mechanisms. The current meta-analysis aims to clarify the robustness of this capacity in infancy within the word segmentation literature. Our analysis reveals a significant, small effect size for conceptual replications of Saffran, Aslin, & Newport (1996), and a nonsignificant effect across all studies that incorporate transitional probabilities to segment words. In both conceptual replications and the broader literature, however, statistical learning is moderated by whether stimuli are naturally produced or synthesized. These findings invite deeper questions about the complex factors that influence statistical learning, and the role of statistical learning in language acquisition.
  • Frank, M. C., Bergelson, E., Bergmann, C., Cristia, A., Floccia, C., Gervain, J., Hamlin, J. K., Hannon, E. E., Kline, M., Levelt, C., Lew-Williams, C., Nazzi, T., Panneton, R., Rabagliati, H., Soderstrom, M., Sullivan, J., Waxman, S., & Yurovsky, D. (2017). A collaborative approach to infant research: Promoting reproducibility, best practices, and theory-building. Infancy, 22(4), 421-435. doi:10.1111/infa.12182.

    Abstract

    The ideal of scientific progress is that we accumulate measurements and integrate these into theory, but recent discussion of replicability issues has cast doubt on whether psychological research conforms to this model. Developmental research—especially with infant participants—also has discipline-specific replicability challenges, including small samples and limited measurement methods. Inspired by collaborative replication efforts in cognitive and social psychology, we describe a proposal for assessing and promoting replicability in infancy research: large-scale, multi-laboratory replication efforts aiming for a more precise understanding of key developmental phenomena. The ManyBabies project, our instantiation of this proposal, will not only help us estimate how robust and replicable these phenomena are, but also gain new theoretical insights into how they vary across ages, linguistic communities, and measurement methods. This project has the potential for a variety of positive outcomes, including less-biased estimates of theoretically important effects, estimates of variability that can be used for later study planning, and a series of best-practices blueprints for future infancy research.
  • Bergmann, C., & Cristia, A. (2016). Development of infants' segmentation of words from native speech: a meta-analytic approach. Developmental Science, 19(6), 901-917. doi:10.1111/desc.12341.

    Abstract

    nfants start learning words, the building blocks of language, at least by 6 months. To do so, they must be able to extract the phonological form of words from running speech. A rich literature has investigated this process, termed word segmentation. We addressed the fundamental question of how infants of different ages segment words from their native language using a meta-analytic approach. Based on previous popular theoretical and experimental work, we expected infants to display familiarity preferences early on, with a switch to novelty preferences as infants become more proficient at processing and segmenting native speech. We also considered the possibility that this switch may occur at different points in time as a function of infants' native language and took into account the impact of various task- and stimulus-related factors that might affect difficulty. The combined results from 168 experiments reporting on data gathered from 3774 infants revealed a persistent familiarity preference across all ages. There was no significant effect of additional factors, including native language and experiment design. Further analyses revealed no sign of selective data collection or reporting. We conclude that models of infant information processing that are frequently cited in this domain may not, in fact, apply in the case of segmenting words from native speech.

    Supplementary material

    desc12341-sup-0001-sup_material.doc
  • Bergmann, C., Cristia, A., & Dupoux, E. (2016). Discriminability of sound contrasts in the face of speaker variation quantified. In Proceedings of the 38th Annual Conference of the Cognitive Science Society. (pp. 1331-1336). Austin, TX: Cognitive Science Society.

    Abstract

    How does a naive language learner deal with speaker variation irrelevant to distinguishing word meanings? Experimental data is contradictory, and incompatible models have been proposed. Here, we examine basic assumptions regarding the acoustic signal the learner deals with: Is speaker variability a hurdle in discriminating sounds or can it easily be ignored? To this end, we summarize existing infant data. We then present machine-based discriminability scores of sound pairs obtained without any language knowledge. Our results show that speaker variability decreases sound contrast discriminability, and that some contrasts are affected more than others. However, chance performance is rare; most contrasts remain discriminable in the face of speaker variation. We take our results to mean that speaker variation is not a uniform hurdle to discriminating sound contrasts, and careful examination is necessary when planning and interpreting studies testing whether and to what extent infants (and adults) are sensitive to speaker differences.

    Supplementary material

    Scripts and data
  • Bergmann, C., Bosch, L. t., Fikkert, P., & Boves, L. (2015). Modelling the Noise-Robustness of Infants’ Word Representations: The Impact of Previous Experience. PLoS One, 10(7): e0132245. doi:10.1371/journal.pone.0132245.

    Abstract

    During language acquisition, infants frequently encounter ambient noise. We present a computational model to address whether specific acoustic processing abilities are necessary to detect known words in moderate noise—an ability attested experimentally in infants. The model implements a general purpose speech encoding and word detection procedure. Importantly, the model contains no dedicated processes for removing or cancelling out ambient noise, and it can replicate the patterns of results obtained in several infant experiments. In addition to noise, we also addressed the role of previous experience with particular target words: does the frequency of a word matter, and does it play a role whether that word has been spoken by one or multiple speakers? The simulation results show that both factors affect noise robustness. We also investigated how robust word detection is to changes in speaker identity by comparing words spoken by known versus unknown speakers during the simulated test. This factor interacted with both noise level and past experience, showing that an increase in exposure is only helpful when a familiar speaker provides the test material. Added variability proved helpful only when encountering an unknown speaker. Finally, we addressed whether infants need to recognise specific words, or whether a more parsimonious explanation of infant behaviour, which we refer to as matching, is sufficient. Recognition involves a focus of attention on a specific target word, while matching only requires finding the best correspondence of acoustic input to a known pattern in the memory. Attending to a specific target word proves to be more noise robust, but a general word matching procedure can be sufficient to simulate experimental data stemming from young infants. A change from acoustic matching to targeted recognition provides an explanation of the improvements observed in infants around their first birthday. In summary, we present a computational model incorporating only the processes infants might employ when hearing words in noise. Our findings show that a parsimonious interpretation of behaviour is sufficient and we offer a formal account of emerging abilities.
  • Van Heugten, M., Bergmann, C., & Cristia, A. (2015). The Effects of Talker Voice and Accent on Young Children's Speech Perception. In S. Fuchs, D. Pape, C. Petrone, & P. Perrier (Eds.), Individual Differences in Speech Production and Perception (pp. 57-88). Bern: Peter Lang.

    Abstract

    Within the first few years of life, children acquire many of the building blocks of their native language. This not only involves knowledge about the linguistic structure of spoken language, but also knowledge about the way in which this linguistic structure surfaces in their speech input. In this chapter, we review how infants and toddlers cope with differences between speakers and accents. Within the context of milestones in early speech perception, we examine how voice and accent characteristics are integrated during language processing, looking closely at the advantages and disadvantages of speaker and accent familiarity, surface-level deviation between two utterances, variability in the input, and prior speaker exposure. We conclude that although deviation from the child’s standard can complicate speech perception early in life, young listeners can overcome these additional challenges. This suggests that early spoken language processing is flexible and adaptive to the listening situation at hand.
  • Bergmann, C., Ten Bosch, L., & Boves, L. (2014). A computational model of the headturn preference procedure: Design, challenges, and insights. In J. Mayor, & P. Gomez (Eds.), Computational Models of Cognitive Processes (pp. 125-136). World Scientific. doi:10.1142/9789814458849_0010.

    Abstract

    The Headturn Preference Procedure (HPP) is a frequently used method (e.g., Jusczyk & Aslin; and subsequent studies) to investigate linguistic abilities in infants. In this paradigm infants are usually first familiarised with words and then tested for a listening preference for passages containing those words in comparison to unrelated passages. Listening preference is defined as the time an infant spends attending to those passages with his or her head turned towards a flashing light and the speech stimuli. The knowledge and abilities inferred from the results of HPP studies have been used to reason about and formally model early linguistic skills and language acquisition. However, the actual cause of infants' behaviour in HPP experiments has been subject to numerous assumptions as there are no means to directly tap into cognitive processes. To make these assumptions explicit, and more crucially, to understand how infants' behaviour emerges if only general learning mechanisms are assumed, we introduce a computational model of the HPP. Simulations with the computational HPP model show that the difference in infant behaviour between familiarised and unfamiliar words in passages can be explained by a general learning mechanism and that many assumptions underlying the HPP are not necessarily warranted. We discuss the implications for conventional interpretations of the outcomes of HPP experiments.
  • Bergmann, C. (2014). Computational models of early language acquisition and the role of different voices. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Tsuji, S., Bergmann, C., & Cristia, A. (2014). Community-Augmented Meta-Analyses: Toward Cumulative Data Assessment. Perspectives on Psychological Science, 9(6), 661-665. doi:10.1177/1745691614552498.

    Abstract

    We present the concept of a community-augmented meta-analysis (CAMA), a simple yet novel tool that significantly facilitates the accumulation and evaluation of previous studies within a specific scientific field. A CAMA is a combination of a meta-analysis and an open repository. Like a meta-analysis, it is centered around a psychologically relevant topic and includes methodological details and standardized effect sizes. As in a repository, data do not remain undisclosed and static after publication but can be used and extended by the research community, as anyone can download all information and can add new data via simple forms. Based on our experiences with building three CAMAs, we illustrate the concept and explain how CAMAs can facilitate improving our research practices via the integration of past research, the accumulation of knowledge, and the documentation of file-drawer studies
  • Bergmann, C., Ten Bosch, L., Fikkert, P., & Boves, L. (2013). A computational model to investigate assumptions in the headturn preference procedure. Frontiers in Psychology, 4: 676. doi:10.3389/fpsyg.2013.00676.

    Abstract

    In this paper we use a computational model to investigate four assumptions that are tacitly present in interpreting the results of studies on infants' speech processing abilities using the Headturn Preference Procedure (HPP): (1) behavioral differences originate in different processing; (2) processing involves some form of recognition; (3) words are segmented from connected speech; and (4) differences between infants should not affect overall results. In addition, we investigate the impact of two potentially important aspects in the design and execution of the experiments: (a) the specific voices used in the two parts on HPP experiments (familiarization and test) and (b) the experimenter's criterion for what is a sufficient headturn angle. The model is designed to be maximize cognitive plausibility. It takes real speech as input, and it contains a module that converts the output of internal speech processing and recognition into headturns that can yield real-time listening preference measurements. Internal processing is based on distributed episodic representations in combination with a matching procedure based on the assumptions that complex episodes can be decomposed as positive weighted sums of simpler constituents. Model simulations show that the first assumptions hold under two different definitions of recognition. However, explicit segmentation is not necessary to simulate the behaviors observed in infant studies. Differences in attention span between infants can affect the outcomes of an experiment. The same holds for the experimenter's decision criterion. The speakers used in experiments affect outcomes in complex ways that require further investigation. The paper ends with recommendations for future studies using the HPP. - See more at: http://journal.frontiersin.org/Journal/10.3389/fpsyg.2013.00676/full#sthash.TUEwObRb.dpuf
  • Bergmann, C., Boves, L., & Ten Bosch, L. (2012). A model of the Headturn Preference Procedure: Linking cognitive processes to overt behaviour. In Proceedings of the 2012 IEEE Conference on Development and Learning and Epigenetic Robotics (IEEE ICDL-EpiRob 2012), San Diego, CA.

    Abstract

    The study of first language acquisition still strongly relies on behavioural methods to measure underlying linguistic abilities. In the present paper, we closely examine and model one such method, the headturn preference procedure (HPP), which is widely used to measure infant speech segmentation and word recognition abilities Our model takes real speech as input, and only uses basic sensory processing and cognitive capabilities to simulate observable behaviour.We show that the familiarity effect found in many HPP experiments can be simulated without using the phonetic and phonological skills necessary for segmenting test sentences into words. The explicit modelling of the process that converts the result of the cognitive processing of the test sentences into observable behaviour uncovered two issues that can lead to null-results in HPP studies. Our simulations show that caution is needed in making inferences about underlying language skills from behaviour in HPP experiments. The simulations also generated questions that must be addressed in future HPP studies.
  • Bergmann, C., Paulus, M., & Fikkert, P. (2012). Preschoolers’ comprehension of pronouns and reflexives: The impact of the task. Journal of Child Language, 39, 777-803. doi:10.1017/S0305000911000298.

    Abstract

    Pronouns seem to be acquired in an asymmetrical way, where children confuse the meaning of pronouns with reflexives up to the age of six, but not vice versa. Children’s production of the same referential expressions is appropriate at the age of four. However, response-based tasks, the usual means to investigate child language comprehension, are very demanding given children’s limited cognitive resources. Therefore, they might affect performance. To assess the impact of the task, we investigated learners of Dutch (three- and four-year-olds) using both eye-tracking, a non-demanding on-line method, and a typical response-based task. Eye-tracking results show an emerging ability to correctly comprehend pronouns at the age of four. A response-based task fails to indicate this ability across age groups, replicating results of earlier studies. Additionally, biases seem to influence the outcome of the response-based task. These results add new evidence to the ongoing debate of the asymmetrical acquisition of pronouns and reflexives and suggest that there is less of an asymmetry than previously assumed.
  • Bergmann, C., Boves, L., & Ten Bosch, L. (2011). Measuring word learning performance in computational models and infants. In Proceedings of the IEEE Conference on Development and Learning, and Epigenetic Robotics. Frankfurt am Main, Germany, 24-27 Aug. 2011.

    Abstract

    In the present paper we investigate the effect of categorising raw behavioural data or computational model responses. In addition, the effect of averaging over stimuli from potentially different populations is assessed. To this end, we replicate studies on word learning and generalisation abilities using the ACORNS models. Our results show that discrete categories may obscure interesting phenomena in the continuous responses. For example, the finding that learning in the model saturates very early at a uniform high recognition accuracy only holds for categorical representations. Additionally, a large difference in the accuracy for individual words is obscured by averaging over all stimuli. Because different words behaved differently for different speakers, we could not identify a phonetic basis for the differences. Implications and new predictions for infant behaviour are discussed.
  • Bergmann, C., Boves, L., & Ten Bosch, L. (2011). Thresholding word activations for response scoring - Modelling psycholinguistic data. In Proceedings of the 12th Annual Conference of the International Speech Communication Association [Interspeech 2011] (pp. 769-772). ISCA.

    Abstract

    In the present paper we investigate the effect of categorising raw behavioural data or computational model responses. In addition, the effect of averaging over stimuli from potentially different populations is assessed. To this end, we replicate studies on word learning and generalisation abilities using the ACORNS models. Our results show that discrete categories may obscure interesting phenomena in the continuous responses. For example, the finding that learning in the model saturates very early at a uniform high recognition accuracy only holds for categorical representations. Additionally, a large difference in the accuracy for individual words is obscured by averaging over all stimuli. Because different words behaved differently for different speakers, we could not identify a phonetic basis for the differences. Implications and new predictions for infant behaviour are discussed.
  • Bergmann, C., Paulus, M., & Fikkert, J. (2010). A closer look at pronoun comprehension: Comparing different methods. In J. Costa, A. Castro, M. Lobo, & F. Pratas (Eds.), Language Acquisition and Development: Proceedings of GALA 2009 (pp. 53-61). Newcastle upon Tyne: Cambridge Scholars Publishing.

    Abstract

    1. Introduction External input is necessary to acquire language. Consequently, the comprehension of various constituents of language, such as lexical items or syntactic and semantic structures should emerge at the same time as or even precede their production. However, in the case of pronouns this general assumption does not seem to hold. On the contrary, while children at the age of four use pronouns and reflexives appropriately during production (de Villiers, et al. 2006), a number of comprehension studies across different languages found chance performance in pronoun trials up to the age of seven, which co-occurs with a high level of accuracy in reflexive trials (for an overview see e.g. Conroy, et al. 2009; Elbourne 2005).
  • Bergmann, C., Gubian, M., & Boves, L. (2010). Modelling the effect of speaker familiarity and noise on infant word recognition. In Proceedings of the 11th Annual Conference of the International Speech Communication Association [Interspeech 2010] (pp. 2910-2913). ISCA.

    Abstract

    In the present paper we show that a general-purpose word learning model can simulate several important findings from recent experiments in language acquisition. Both the addition of background noise and varying the speaker have been found to influence infants’ performance during word recognition experiments. We were able to replicate this behaviour in our artificial word learning agent. We use the results to discuss both advantages and limitations of computational models of language acquisition.
  • Gubian, M., Bergmann, C., & Boves, L. (2010). Investigating word learning processes in an artificial agent. In Proceedings of the IXth IEEE International Conference on Development and Learning (ICDL). Ann Arbor, MI, 18-21 Aug. 2010 (pp. 178 -184). IEEE.

    Abstract

    Researchers in human language processing and acquisition are making an increasing use of computational models. Computer simulations provide a valuable platform to reproduce hypothesised learning mechanisms that are otherwise very difficult, if not impossible, to verify on human subjects. However, computational models come with problems and risks. It is difficult to (automatically) extract essential information about the developing internal representations from a set of simulation runs, and often researchers limit themselves to analysing learning curves based on empirical recognition accuracy through time. The associated risk is to erroneously deem a specific learning behaviour as generalisable to human learners, while it could also be a mere consequence (artifact) of the implementation of the artificial learner or of the input coding scheme. In this paper a set of simulation runs taken from the ACORNS project is investigated. First a look `inside the box' of the learner is provided by employing novel quantitative methods for analysing changing structures in large data sets. Then, the obtained findings are discussed in the perspective of their ecological validity in the field of child language acquisition.

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