Multi-Tier Annotations in the Verbmobil Corpus

In very large and diverse scientific projects where as different groups as linguists and engineers with different intentions work on the same signal data or its orthographic transcript and annotate new valuable information, it will not be easy to build a homogeneous corpus. We will describe how this can be achieved, considering the fact that some of these annotations have not been updated properly, or are based on erroneous or deliberately changed versions of the basis transcription. We used an algorithm similar to dynamic programming to detect differences between the transcription on which the annotation depends and the reference transcription for the whole corpus. These differences are automatically mapped on a set of repair operations for the transcriptions such as splitting compound words and merging neighbouring words. On the basis of these operations the correction process in the annotation is carried out. It always depends on the type of the annotation as well as on the position and the nature of the difference, whether a correction can be carried out automatically or has to be fixed manually. Finally we present a investigation in which we exploit the multi-tier annotations of the Verbmobil corpus to find out how breathing is correlated with prosodic-syntactic boundaries and dialog acts. 1

Quantification of Evaporation and Drainage Processes in Unsaturated Porous Media Using Magnetic Resonance Imaging

The water loss in packed beds was studied spatially and time‐resolved via magnetic resonance imaging on the pore scale. The packed beds were measured under water‐saturated and unsaturated conditions, while the magnetic resonance method allowed a quantitative differentiation between air, liquid, and solid phases exploring the native contrast of the named phases without additional contrast agents. Beside a qualitative image comparison, subsequent quantitative image processing allowed for a detailed spatially resolved determination of water distribution, the differentiation between water transport processes, and the quantification of liquid clusters in 3‐D. Results are presented for two packed beds that show significant differences in their evaporation and drainage dynamics, which are mainly determined by the physical properties of the packed beds. The water loss of the packed bed of 2–4mmquartz particles reached a level below interpretability after 18.2 hr; meanwhile, a successive decrease of the largest liquid cluster volume from 82.5 to 0.7 mm$^{3}$ was observed. The water content of the packed bed of 2 mm glass spheres was still observable after 70.9 hr. During the experiment, no significant changes in the structure of the liquid clusters were measured. The current work displays the applicability of magnetic resonance imaging for porescale investigations without the addition of contrast agents

Machine Learning of Probabilistic Phonological Pronunciation Rules from the Italian CLIPS Corpus

A blending of phonological concepts and technical analysis is proposed to yield a better modeling and understanding of phonological processes. Based on the manual segmentation and labeling of the Italian CLIPS corpus we automatically derive a probabilistic set of phonological pronunciation rules: a new alignment technique is used to map the phonological form of spontaneous sentences onto the phonetic surface form. A machine-learning algorithm then calculates a set of phonologi- cal replacement rules together with their conditional probabilities. A critical analysis of the resulting probabilistic rule set is presented and discussed with regard to regional Italian accents. The rule set presented here is also applied in the newly published web-service WebMAUS that allows a user to segment and phonetically label Italian speech via a simple web-interface

Predictability of the effects of phoneme merging on speech recognition performance by quantifying phoneme relations

To investigate whether the impact of phoneme merging on recognition rate can be predicted, different measures to quantify the relationship between two phonemes a and b were compared: (1) the functional load of their opposition, (2) the bigram type preservation, (3) their information radius, (4) their distance within an information gain tree induced from a distinctive feature matrix, and (5) the symmetric Kullback-Leibler divergence. For each of 25 phoneme pairs we trained a speech recognizer on data in which the respective pair was merged. Based on correlation analyses and predictor selection in stepwise regression modelling we found that the impact of phoneme merging on accuracy can tentatively be captured in terms of functional load and tree distance between the merged phonemes

Blockade der Organisationsentwicklung im öffentlichen Sektor: der Botanische Garten in Berlin als Fallbeispiel

Die gegenwärtigen Transformationsprozesse im öffentlichen Sektor werden unter anderem durch das Konzept der betrieblichen Rationalisierungsmuster erklärt, das vor allem an mikropolitische Ansätze anknüpft. Dabei werden Organisationen als Handlungs- und Entscheidungsfelder verstanden, die aufgrund ihrer Strukturen und Sozialbeziehungen sowie der daraus entstehenden Interaktionsprozesse spezifische betriebliche Rationalisierungsmuster hervorbringen. Im vorliegenden Beitrag wird zum besseren Verständnis von Reorganisationsprozessen im öffentlichen Sektor über einige Erkenntnisse berichtet, die im Rahmen des Forschungs- und Entwicklungsprojekts 'Beteiligungsorientierte Veränderung der Arbeitsorganisation und der betriebsinternen Kommunikation in drei Bereichen der Zentraleinrichtung Botanischer Garten Botanisches Museum (ZE BGBM) Berlin' gewonnen wurden. Es werden die Wandelkonzepte skizziert, mit denen das Land Berlin seinen Landeshaushalt zu konsolidieren versucht, und die Partizipationsmöglichkeiten und Handlungskonstellationen bei der Restrukturierung der ZE BGBM erörtert. Abschließende Überlegungen beziehen sich auf die Folgen der betrieblichen Rationalisierungsmuster in Berlin. (ICI2

Probing speech emotion recognition transformers for linguistic knowledge

Large, pre-trained neural networks consisting of self-attention layers (transformers) have recently achieved state-of-the-art results on several speech emotion recognition (SER) datasets. These models are typically pre-trained in self-supervised manner with the goal to improve automatic speech recognition performance -- and thus, to understand linguistic information. In this work, we investigate the extent in which this information is exploited during SER fine-tuning. Using a reproducible methodology based on open-source tools, we synthesise prosodically neutral speech utterances while varying the sentiment of the text. Valence predictions of the transformer model are very reactive to positive and negative sentiment content, as well as negations, but not to intensifiers or reducers, while none of those linguistic features impact arousal or dominance. These findings show that transformers can successfully leverage linguistic information to improve their valence predictions, and that linguistic analysis should be included in their testing

Extracting Atoms on Demand with Lasers

We propose a scheme that allows to coherently extract cold atoms from a reservoir in a deterministic way. The transfer is achieved by means of radiation pulses coupling two atomic states which are object to different trapping conditions. A particular realization is proposed, where one state has zero magnetic moment and is confined by a dipole trap, whereas the other state with non-vanishing magnetic moment is confined by a steep microtrap potential. We show that in this setup a predetermined number of atoms can be transferred from a reservoir, a Bose-Einstein condensate, into the collective quantum state of the steep trap with high efficiency in the parameter regime of present experiments.Comment: 11 pages, 8 figure