Prosody, focus, and focal structure : some remarks on methodology

Prosody falls between several established fields as e.g. phonetics, phonology, syntax, and dialogue structure. It is therefore prone to misconceptions: often, its relevancy is overestimated, and often, it is underestimated. The traditional method in linguistics in general and in phonology in particular is the construction and evaluation of sometimes rather complex examples based on the intuition of the linguist. This intuition is replaced by more or less naive and thus non-expert subjects and inferential statistics in experimental phonetics but the examples, i.e. the experimental material, are often rather complex as well. It is a truism that in both cases, conclusions are made on an "as if\u27; basis: as if a final proof had been found that the phenomenon A really exists regularily in the language B. In fact, it only can be proven that the phenomenon A sometimes can be detected in the production of some speakers of a variety of language B. This dilemma matters if prosody has to be put into practice, e.g. in automatic speech and language processing. In this field, large speech databases are already available for English and will be available for other languages as e.g. German in the near future. At least in the beginning, the problems that can - hopefully - be solved with the help of such databases might look trivial and thus not interesting - a step backwards and not forwards. "As if\u27; statements (concerning, e.g., narrow vs. broad focus) and problems that are trivial at face value (concerning, e.g., the relationship between phrasing units and accentuation and the ontology of sentence accent) will be illustrated with own material. I will argue that such trivial problems have to be dealt with in the beginning, and that they can constitute the very basis for the proper treatment of more far reaching and complex problems

Commentary on Liechtenstein Company Law

recent development

Commentary on Liechtenstein Company Law

recent development

Impact of Vaccine Availability on the Number of Children Vaccinated and Under-Five Mortality in Tanzania

Stockouts have previously been reported to interrupt immunization services in low-and-middle income countries. However, there has been little research to understand the direct impact of stockouts on the number of children immunized and no research to understand the impact on under-five mortality. Using panel data from Tanzania’s Vaccine Information Management System training program, a regression model with fixed and random effects is used to analyze the effect of stockouts on the number of children immunized. The Lives Saved Tool® is used to estimate the effect of stockouts on under-five mortality. The results suggest that stockouts have a statistically significant impact on the number of children immunized for most vaccines in the current month and for several months after the stockout. No impact was found on under-five mortality. However, due to limitations in this analysis, this relationship should be further explored

Assessing the Prosody of Non-Native Speakers of English: Measures and Feature Sets

In this paper, we describe a new database with audio recordings of non-native (L2) speakers of English, and the perceptual evaluation experiment conducted with native English speakers for assessing the prosody of each recording. These annotations are then used to compute the gold standard using different methods, and a series of regression experiments is conducted to evaluate their impact on the performance of a regression model predicting the degree of Abstract naturalness of L2 speech. Further, we compare the relevance of different feature groups modelling prosody in general (without speech tempo), speech rate and pauses modelling speech tempo (fluency), voice quality, and a variety of spectral features. We also discuss the impact of various fusion strategies on performance.Overall, our results demonstrate that the prosody of non-native speakers of English as L2 can be reliably assessed using supra- segmental audio features; prosodic features seem to be the most important ones

Creating a Tudor Musical Miscellany: The McGhie/Tenbury 389 Partbooks

The best-known Tudor manuscript partbooks tend to be complete or near-complete sets, associated with known individuals, elegantly copied, and with a clear repertorial focus. Yet such manuscripts are not the norm among extant partbooks. Rather most are obscure in origin, the product of workaday copying, and survive as orphans or partial sets. They are miscellanies with wide-ranging contents, complex and seemingly chaotic in their compilation, and their challenges have tended to deter scholarly attention. This article focuses on one particular miscellany from which two partbooks survive—the privately owned McGhie partbook and Bodleian Library Tenbury MS 389—to explore what such collections can reveal about the methods and habits of compilers and the circulation of music. These partbooks were assembled in a series of stages that demonstrate several different strategies for the collection and selection of pieces, methods for organizing scribal labour, and the influence of musical print culture on manuscript production

Integrating Syntactic and Prosodic Information for the Efficient Detection of Empty Categories

We describe a number of experiments that demonstrate the usefulness of prosodic information for a processing module which parses spoken utterances with a feature-based grammar employing empty categories. We show that by requiring certain prosodic properties from those positions in the input where the presence of an empty category has to be hypothesized, a derivation can be accomplished more efficiently. The approach has been implemented in the machine translation project VERBMOBIL and results in a significant reduction of the work-load for the parser.Comment: To appear in the Proceedings of Coling 1996, Copenhagen. 6 page

I hear you eat and speak: automatic recognition of eating condition and food type, use-cases, and impact on ASR performance

We propose a new recognition task in the area of computational paralinguistics: automatic recognition of eating conditions in speech, i. e., whether people are eating while speaking, and what they are eating. To this end, we introduce the audio-visual iHEARu-EAT database featuring 1.6 k utterances of 30 subjects (mean age: 26.1 years, standard deviation: 2.66 years, gender balanced, German speakers), six types of food (Apple, Nectarine, Banana, Haribo Smurfs, Biscuit, and Crisps), and read as well as spontaneous speech, which is made publicly available for research purposes. We start with demonstrating that for automatic speech recognition (ASR), it pays off to know whether speakers are eating or not. We also propose automatic classification both by brute-forcing of low-level acoustic features as well as higher-level features related to intelligibility, obtained from an Automatic Speech Recogniser. Prediction of the eating condition was performed with a Support Vector Machine (SVM) classifier employed in a leave-one-speaker-out evaluation framework. Results show that the binary prediction of eating condition (i. e., eating or not eating) can be easily solved independently of the speaking condition; the obtained average recalls are all above 90%. Low-level acoustic features provide the best performance on spontaneous speech, which reaches up to 62.3% average recall for multi-way classification of the eating condition, i. e., discriminating the six types of food, as well as not eating. The early fusion of features related to intelligibility with the brute-forced acoustic feature set improves the performance on read speech, reaching a 66.4% average recall for the multi-way classification task. Analysing features and classifier errors leads to a suitable ordinal scale for eating conditions, on which automatic regression can be performed with up to 56.2% determination coefficient