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Glossolalia can be regarded as an instance of speech production in which practitioners produce syllables in seemingly random sequences. However, a closer inspection of glossalalia's statistical properties reveals that sequences show a Zipfian pattern similar to natural languages, with some syllables being more probable than others. It is well established that statistical properties of sequences are implicitly learned, and that these statistical properties correlate with changes in kinematic and speech behavior. For speech, this means that more predictable items are phonetically shorter. Accordingly, we hypothesized for glossolalia that if practitioners have learned a serial pattern in glossolalia in the same manner as in natural languages, its statistical properties should correlate with its phonetic characteristics. Our hypothesis was supported. We find significantly shorter syllables associated with higher syllable probabilities in glossolalia. We discuss this finding in relation to theories about the sources of probability-related changes in the speech signal. [ABSTRACT FROM AUTHOR]

Sequence learning is fundamental to a wide range of cognitive functions. Explaining how sequences—and the relations between the elements they comprise—are learned is a fundamental challenge to cognitive science. However, although hundreds of articles addressing this question are published each year, the actual learning mechanisms involved in the learning of sequences are rarely investigated. We present three experiments that seek to examine these mechanisms during a typing task. Experiments 1 and 2 tested learning during typing single letters on each trial. Experiment 3 tested for "chunking" of these letters into "words." The results of these experiments were used to examine the mechanisms that could best account for them, with a focus on two particular proposals: statistical transitional probability learning and discriminative error‐driven learning. Experiments 1 and 2 showed that error‐driven learning was a better predictor of response latencies than either n‐gram frequencies or transitional probabilities. No evidence for chunking was found in Experiment 3, probably due to interspersing visual cues with the motor response. In addition, learning occurred across a greater distance in Experiment 1 than Experiment 2, suggesting that the greater predictability that comes with increased structure leads to greater learnability. These results shed new light on the mechanism responsible for sequence learning. Despite the widely held assumption that transitional probability learning is essential to this process, the present results suggest instead that the sequences are learned through a process of discriminative learning, involving prediction and feedback from prediction error. [ABSTRACT FROM AUTHOR]

Recent experiments showed that the perception of vowel length by German listeners exhibits the characteristics of categorical perception. The present study sought to find the neural activity reflecting categorical vowel length and the short-long boundary by examining the processing of non-contrastive durations and categorical length using MEG. Using disyllabic words with varying /a/-durations and temporally-matched nonspeech stimuli, we found that each syllable elicited an "M50"/"M100"-complex. The "M50"-amplitude to the second syllable varied along the durational continuum, possibly reflecting the mapping of duration onto a rhythm representation. Categorical length was reflected by an additional response elicited when vowel duration exceeded the short-long boundary. This was interpreted to reflect the integration of an additional timing unit for long in contrast to short vowels. Unlike to speech, responses to short nonspeech durations lacked a "M100" to the first and "M50" to the second syllable, indicating different integration windows for speech and nonspeech signals. (Contains 2 tables and 6 figures.)

Recent evidence indicates that a word's paradigmatic neighbors affect production. However, these findings have mostly been obtained in careful laboratory settings using words in isolation, and thus ignoring potential effects that may arise from the syntagmatic context, which is typically present in spontaneous speech. The current corpus analysis investigates paradigmatic and syntagmatic effects in Estonian spontaneous speech. Following work on English, we focus on the duration of inflected and uninflected word-final /-s/ in content words, while simultaneously investigating whole words. Our analyses reveal three points. First, we find an effect of realized inflectional paradigm size, such that smaller paradigms actively used by the speakers lead to longer durations. Second, higher conditional probability is associated with shorter word forms and shorter segments. Finally, we do not directly replicate previous work on effects of inflectional status as in English word-final /-s/. Instead, we find that inflectional status interacts with conditional probability. We discuss the results in light of models of speech production and how they account for morphologically complex words and their paradigmatic neighbors. [ABSTRACT FROM AUTHOR]

Grammatical knowledge has often been investigated in wug tests, in which participants inflect pseudo-words. It was argued that in inflecting these pseudo-words, speakers apply their knowledge of word formation. However, it remains unclear what exactly this knowledge is and how it is learned. According to one theory, the knowledge is best characterised as abstractions that specify how units are combined. Another theory maintains that it is best characterised by memory-based analogy. In both cases the knowledge is learned by association based on positive evidence alone. In this paper, we model the classification of pseudo-words to Maltese plurals using a shallow neural network trained with an error-driven learning algorithm. We demonstrate that the classifications mirror those of Maltese speakers in a wug test. Our results indicate that speakers rely on gradient knowledge of a relation between the phonetics of whole words and plural classes, which is learned in an error-driven way. [ABSTRACT FROM AUTHOR]

Last year, 2022, marked the 50th anniversary of the Rescorla-Wagner learning equations – a landmark in the development of learning theory. Originally based on animal learning, the equations and error-driven learning models as a whole were rapidly adopted and applied in several areas of human psychology. While language acquisition research initially took a different path, interest in the role of error-driven learning in language is growing. With the aim of strengthening this emerging research field, sparking discussion and cross-fertilisation of ideas across linguistics, psychology and cognate fields, this Special Issue presents nine papers that address the role of error-driven learning in language. The papers investigate a wide range of subfields of linguistics, and include two review articles, in addition to computational modelling and experimental research. The collection thus serves both as an introduction for those new to the subject and as an overview for those already working in the field. [ABSTRACT FROM AUTHOR]

Maltese is a prime example of a language that emerged through extensive language contact, joining the two linguistic worlds of Semitic and Italo-Romance languages. Previous studies have shown this shared origin on the basis of hands-on comparative methods. However, such approaches may be biased by the researchers perspective and the selected material. To avoid this bias, we employed a naive computational method that classifies words on the basis of their phonotactics. Specifically, we trained a simple two-layer neural network on Tunisian and Italian nouns, i.e. the languages that Maltese emerged from. We used the trained network to classify Maltese nouns based on their phonotactic characteristics as either of Tunisian or of Italian origin. Overall, the network is capable of correctly classifying Maltese nouns as belonging to either of the original languages. Moreover, we find that the classification depends on whether a noun has a sound or broken plural. By manipulating the segment identity in the training input, we found that consonants are more important for the classification of Maltese nouns than vowels. While our results replicate previous comparative studies, they also demonstrate that a more fine grained classification of a language's origin can be based on individual words and morphological classes. [ABSTRACT FROM AUTHOR]

Word-based models of morphology propose that complex words are stored without reference to morphemes. One of the questions that arises is whether information about word forms alone is enough to determine a noun's number from its form. We take up this question by modelling the classification and production of the Maltese noun plural system, using models that do not assume morphemic representations. We use the Tilburg Memory-Based Learner, a computational implementation of exemplar theory and the Naive Discriminative Learner, an implementation of Word and Paradigm, for classification. Both models classify Maltese nouns well. In their current implementations, TiMBL and NDL cannot concatenate sequences of phones that result in word forms. We used two neural networks architectures (LSTM and GRU) to model the production of plurals. We conclude that the Maltese noun plural system can be modelled on the basis of whole words without morphemes, supporting word-based models of morphology. [ABSTRACT FROM AUTHOR]

Repeating the movements associated with activities such as drawing or sports typically leads to improvements in kinematic behavior: these movements become faster, smoother, and exhibit less variation. Likewise, practice has also been shown to lead to faster and smoother movement trajectories in speech articulation. However, little is known about its effect on articulatory variability. To address this, we investigate the extent to which repetition and predictability influence the articulation of the frequent German word "sie" [zi] (they). We find that articulatory variability is proportional to speaking rate and the duration of [zi], and that overall variability decreases as [zi] is repeated during the experiment. Lower variability is also observed as the conditional probability of [zi] increases, and the greatest reduction in variability occurs during the execution of the vocalic target of [i]. These results indicate that practice can produce observable differences in the articulation of even the most common gestures used in speech. [ABSTRACT FROM AUTHOR]

Recent research on the acoustic realization of affixes has revealed differences between phonologically homophonous affixes, e.g. the different kinds of final [s] and [z] in English (Plag, Homann & Kunter 2017, Zimmermann 2016a). Such results are unexpected and unaccounted for in widely accepted post-Bloomfieldian item-and-arrangement models (Hockett 1954), which separate lexical and post-lexical phonology, and in models which interpret phonetic effects as consequences of different prosodic structure. This paper demonstrates that the differences in duration of English final S as a function of the morphological function it expresses (non-morphemic, plural, third person singular, genitive, genitive plural, cliticized has, and cliticized is) can be approximated by considering the support for these morphological functions from the words' sublexical and collocational properties. We estimated this support using naïve discriminative learning and replicated previous results for English vowels (Tucker, Sims & Baayen 2019), indicating that segment duration is lengthened under higher functional certainty but shortened under functional uncertainty. We discuss the implications of these results, obtained with a wide learning network that eschews representations for morphemes and exponents, for models in theoretical morphology as well as for models of lexical processing. [ABSTRACT FROM AUTHOR]

Recent research has revealed substantial between-speaker variation in speech rhythm, which in effect refers to the coordination of consonants and vowels over time. In the current proof-of-concept study, the hypothesis was investigated that these idiosyncrasies arise, in part, from differences in the tongue's movement amplitude. Speech rhythm was parameterized by means of the percentage over which speech is vocalic (%V) in the German pronoun "sie" [ziː]. The findings support the hypothesis: all else being equal, idiosyncratic %V values behaved proportionally to a speaker's tongue movement area. This research underlines the importance of studying language-external factors, such as a speaker's individual tongue movement behavior, to investigate variation in temporal coordination. [ABSTRACT FROM AUTHOR]

Highlights • Regression results in suppression and enhancement when fitted to collinear data sets. • Three methods to manage collinearity in data sets are presented. • Jointly, they allow to understand the quantitative structure of empirical data. Abstract When multiple correlated predictors are considered jointly in regression modeling, estimated coefficients may assume counterintuitive and theoretically uninterpretable values. We survey several statistical methods that implement strategies for the analysis of collinear data: regression with regularization (the elastic net), supervised component generalized linear regression, and random forests. Methods are illustrated for a data set with a wide range of predictors for segment duration in a German speech corpus. Results broadly converge, but each method has its own strengths and weaknesses. Jointly, they provide the analyst with somewhat different but complementary perspectives on the structure of collinear data. [ABSTRACT FROM AUTHOR]

Many studies report shorter acoustic durations, more coarticulation and reduced articulatory targets for frequent words. This study investigates a factor ignored in discussions on the relation between frequency and phonetic detail, namely, that motor skills improve with experience. Since frequency is a measure of experience, it follows that frequent words should show increased articulatory proficiency. We used EMA to test this prediction on German inflected verbs with [a] as stem vowels. Modeling median vertical tongue positions with quantile regression, we observed significant modulation by frequency of the U-shaped trajectory characterizing the articulation of the [a:]. These modulations reflect two constraints, one favoring smooth trajectories through anticipatory coarticulation, and one favoring clear articulation by realizing lower minima. The predominant pattern across sensors, exponents, and speech rate suggests that the constraint of clarity dominates for lower-frequency words. For medium-frequency words, the smoothness constraint leads to a raising of the trajectory. For the higher-frequency words, both constraints are met simultaneously, resulting in low minima and stronger coarticulation. These consequences of motor practice for articulation challenge both the common view that a higher-frequency of use comes with more articulatory reduction, and cognitive models of speech production positing that articulation is post-lexical. [ABSTRACT FROM AUTHOR]

Sound units play a pivotal role in cognitive models of auditory comprehension. The general consensus is that during perception listeners break down speech into auditory words and subsequently phones. Indeed, cognitive speech recognition is typically taken to be computationally intractable without phones. Here we present a computational model trained on 20 hours of conversational speech that recognizes word meanings within the range of human performance (model 25%, native speakers 20–44%), without making use of phone or word form representations. Our model also generates successfully predictions about the speed and accuracy of human auditory comprehension. At the heart of the model is a ‘wide’ yet sparse two-layer artificial neural network with some hundred thousand input units representing summaries of changes in acoustic frequency bands, and proxies for lexical meanings as output units. We believe that our model holds promise for resolving longstanding theoretical problems surrounding the notion of the phone in linguistic theory. [ABSTRACT FROM AUTHOR]