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In our study we use the experimental framework of priming to manipulate our subjects’ expectations of syllable prominence in sentences with a well-defined syntactic and phonological structure. It shows that it is possible to prime prominence patterns and that priming leads to significant differences in the judgment of syllable prominence.
This paper describes work directed towards the development of a syllable prominence-based prosody generation functionality for a German unit selection speech synthesis system. A general concept for syllable prominence-based prosody generation in unit selection synthesis is proposed. As a first step towards its implementation, an automated syllable prominence annotation procedure based on acoustic analyses has been performed on the BOSS speech corpus. The prominence labeling has been evaluated against an existing annotation of lexical stress levels and manual prominence labeling on a subset of the corpus. We discuss methods and results and give an outlook on further implementation steps.
In previous research we showed that the priming paradigm can be used to significantly alter the prominence ratings of subjects. In that study we only looked at the changes in the subjects’ ratings. In the present study, we analyzed the acoustic parameters of the stimuli used in the priming study and investigated the correlation between prominence ratings and acoustic parameters. The results show that priming has a significant effect on these correlations. The contribution of acoustic features on perceived prominence was found to depend on the prominence pattern. If a dominantly prominent syllable is present in a given utterance, f0 and intensity contribute most to the perceived prominence, while duration contributes most when no syllable is dominantly prominent.
Streefkerk defines prominence as the perceptually outstanding parts in spoken language. An optimal rating scale for syllable prominence has not been found yet. This paper evaluates a 4-point, an 11-point, a 31-point, and a continuous scale for the rating of syllable prominence and gives support for scales using a higher number of levels. Priming effects found by Arnold, et al., could only be replicated using the 31-point scale.
Prominence has been widely studied on the word level and the syllable level. An extensive study comparing the two approaches is missing in the literature. This study investigates how word and syllable prominence relate to each other in German. We find that perceptual ratings based on the word level are more extreme than those based on the syllable level. The correlations between word prominence and acoustic features are greater than the correlations between syllable prominence and acoustic features.
A frequently replicated finding is that higher frequency words tend to be shorter and contain more strongly reduced vowels. However, little is known about potential differences in the articulatory gestures for high vs. low frequency words. The present study made use of electromagnetic articulography to investigate the production of two German vowels, [i] and [a], embedded in high and low frequency words. We found that word frequency differently affected the production of [i] and [a] at the temporal as well as the gestural level. Higher frequency of use predicted greater acoustic durations for long vowels; reduced durations for short vowels; articulatory trajectories with greater tongue height for [i] and more pronounced downward articulatory trajectories for [a]. These results show that the phonological contrast between short and long vowels is learned better with experience, and challenge both the Smooth Signal Redundancy Hypothesis and current theories of German phonology.
The perception of syllable prominence depends to a limited extent on the acoustic properties of the speech signal in question. Psychoacoustic factors are involved as well. Thus, research often relies on two types of data: subjective prominence ratings collected in perception experiments and acoustic measures. A problem with the rating data is noise resulting from individual approaches to the rating task. This paper addresses the question of how this noise can be reduced by normalization, evaluating 12 normalization methods. In a perception experiment, prominence ratings concerning German read speech were collected. From the raw rating data 12 different ‘mirror’ data-sets were computed according to the 12 methods. Each mirror data-set was correlated with the same set of underlying acoustic data. The multiple regression setup included raw syllable duration as well as within-syllable maximum F0 and intensity. Adjusted r2-values could beraised considerably with selected methods.
The instructions under which raters quantify syllable prominence perception need to be simple in order to maintain immediate reactions. This leads to noise in the rating data that can be dealt with by normalization, e.g. setting central tendency = 0 and dispersion = 1 (as in Z-score normalization). Questions arise such as: Which parameter is adequate here to capture central tendency? Which reference distribution should the normalization be based on? In this paper 16 different normalization methods are evaluated. In a perception experiment using German read speech (prose and poetry), syllable prominence ratings were collected. From the rating data 16 complete “mirror” data-sets were computed according to the 16 methods. Each mirror data-set was correlated with the same set of measures from the underlying acoustic data, focusing on raw syllable duration which is seen as a rather straightforward acoustic aspect of syllable prominence. Correlation coefficients could be raised considerably by selected methods.
The perception of prosodic prominence is influenced by different sources like different acoustic cues, linguistic expectations and context. We use a generalized additive model and a random forest to model the perceived prominence on a corpus of spoken German. Both models are able to explain over 80% of the variance. While the random forests give us some insights on the relative importance of the cues, the general additive model gives us insights on the interaction between different cues to prominence.
Die vorliegende Dissertation beschäftigt sich mit verschieden Methoden zur Erhebung von perzeptuellen Prominenzurteilen von naiven Hörern im Deutschen. Es werden zwei Experimente vorgestellt, die sich zum einen mit der Verwendung von verschiedenen Skalen, zum anderen mit der Verwendung von unterschiedlichen Bewertungsebenen zur Beurteilung von perzeptueller Prominenz beschäftigen. Die Ergebnisse zeigen, dass Ergebnisse von Studien, welche auf unterschiedlichen Erhebungstechniken beruhen nicht ohne weiteres vergleichbar sind. Die Arbeit untersucht außerdem die Effekte einer Normalisierung der Prominenzurteile. Die Dissertation schließt mit einem Ausblick für zukünftige Studien. Hierbei werden hauptsächlich die vielfältigen Interaktionen von verschiedenen Quellen und dem Kontext bei der Beurteilung der perzeptuellen Prominenz adressiert.
A frequently replicated finding is that higher frequency words tend to be shorter and contain more strongly reduced vowels. However, little is known about potential differences in the articulatory gestures for high vs. low frequency words. The present study made use of electromagnetic articulography to investigate the production of two German vowels, [i] and [a], embedded in high and low frequency words. We found that word frequency differently affected the production of [i] and [a] at the temporal as well as the gestural level. Higher frequency of use predicted greater acoustic durations for long vowels; reduced durations for short vowels; articulatory trajectories with greater tongue height for [i] and more pronounced downward articulatory trajectories for [a]. These results show that the phonological contrast between short and long vowels is learned better with experience, and challenge both the Smooth Signal Redundancy Hypothesis and current theories of German phonology.
This paper presents newly developed guidelines for prosodic annotation of German as a consensus system agreed upon by German intonologists. The DIMA system is rooted in the framework of autosegmental-metrical phonology. One important goal of the consensus is to make exchanging data between groups easier since German intonation is currently annotated according to different models. To this end, we aim to provide guidelines that are easy to learn. The guidelines were evaluated running an inter-annotator reliability study on three different speech styles (read speech, monologue and dialogue). The overall high κ between 0.76 and 0.89 (depending on the speech style) shows that the DIMA conventions can be applied successfully.
The present study introduces articulography, the measurement of the position of tongue and lips during speech, as a promising method to the study of dialect variation. By using generalized additive modeling to analyze articulatory trajectories, we are able to reliably detect aggregate group differences, while simultaneously taking into account the individual variation across dozens of speakers. Our results on the basis of Dutch dialect data show clear differences between the southern and the northern dialect with respect to tongue position, with a more frontal tongue position in the dialect from Ubbergen (in the southern half of the Netherlands) than in the dialect of Ter Apel (in the northern half of the Netherlands). Thus articulography appears to be a suitable tool to investigate structural differences in pronunciation at the dialect level.
The current paper presents a corpus containing 35 dialogues of spontaneously spoken southern German, including half an hour of articulography for 13 of the speakers. Speakers were seated in separate recording chambers, mimicking a telephone call, and recorded on individual audio channels. The corpus provides manually corrected word boundaries and automatically aligned segment boundaries. Annotations are provided in the Praat format. In addition to audio recordings, speakers filled out a detailed questionnaire, assessing among others their audio-visual consumption habits.
The present study uses electromagnetic articulography, by which the position of tongue and lips during speech is measured, for the study of dialect variation. By using generalized additive modeling to analyze the articulatory trajectories, we are able to reliably detect aggregate group differences, while simultaneously taking into account the individual variation of dozens of speakers. Our results show that two Dutch dialects show clear differences in their articulatory settings, with generally a more anterior tongue position in the dialect from Ubbergen in the southern half of the Netherlands than in the dialect of Ter Apel in the northern half of the Netherlands. A comparison with formant-based acoustic measurements further reveals that articulography is able to reveal interesting structural articulatory differences between dialects which are not visible when only focusing on the acoustic signal.
Multinomial processing tree (MPT) models are a class of measurement models that account for categorical data by assuming a finite number of underlying cognitive processes. Traditionally, data are aggregated across participants and analyzed under the assumption of independently and identically distributed observations. Hierarchical Bayesian extensions of MPT models explicitly account for participant heterogeneity by assuming that the individual parameters follow a continuous hierarchical distribution.We provide an accessible introduction to hierarchical MPT modeling and present the user-friendly and comprehensive R package TreeBUGS, which implements the two most important hierarchical MPT approaches for participant heterogeneity—the beta-MPT approach (Smith & Batchelder, Journal of Mathematical Psychology 54:167-183, 2010) and the latent-trait MPT approach (Klauer, Psychometrika 75:70-98, 2010). TreeBUGS reads standard MPT model files and obtains Markov-chain Monte Carlo samples that approximate the posterior distribution. The functionality and output are tailored to the specific needs of MPT modelers and provide tests for the homogeneity of items and participants, individual and group parameter estimates, fit statistics, and within- and between-subjects comparisons, as well as goodness-of-fit and summary plots. We also propose and implement novel statistical extensions to include continuous and discrete predictors (as either fixed or random effects) in the latent-trait MPT model.
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.
The relation between speed and curvature provides a characterization of the spatio-temporal orchestration of kinematic movements. For hand movements, this relation has been reported to follow a power law with exponent -1/3. The same power law has been claimed to govern articulatory movements. We studied the functional form of speed as predicted by curvature using electromagnetic articulography, focusing on three sensors: the tongue tip, the tongue body, and the lower lip. Of specific interest to us was the question of whether the speed-curvature relation is modified by articulatory practice, gauged with words’ frequencies of occurrence. Although analyses imposing linearity a priori indeed supported a power law, relaxation of this linearity assumption revealed that the effect of curvature on speed levels off substantially for lower values of curvature. A modification of the power law is proposed that takes this curvature into account. Furthermore, controlling statistically for number of phones and word duration, we observed that the speed-curvature function was further modulated by an interaction of lexical frequency by curvature, such that for increasing frequency, speed decreased slightly for low curvatures while it increased slightly for high curvatures. The modulation of the balance between speed and curvature by lexical frequency provides further evidence that the skill of articulation improves with practice on a word-to-word basis, and challenges theories of speech production.
This paper addresses long-term archival for large corpora. Three aspects specific to language resources are focused, namely (1) the removal of resources for legal reasons, (2) versioning of (unchanged) objects in constantly growing resources, especially where objects can be part of multiple releases but also part of different collections, and (3) the conversion of data to new formats for digital preservation. It is motivated why language resources may have to be changed, and why formats may need to be converted. As a solution, the use of an intermediate proxy object called a signpost is suggested. The approach will be exemplified with respect to the corpora of the Leibniz Institute for the German Language in Mannheim, namely the German Reference Corpus (DeReKo) and the Archive for Spoken German (AGD).