Phonetic and prosodic analysis of speech

In order to cope with the problems of spontaneous speech (including, for example, hesitations and non-words) it is necessary to extract from the speech signal all information it contains. Modeling of words by segmental units should be supported by suprasegmental units since valuable information is represented in the prosody of an utterance. We present an approach to flexible and efficient modeling of speech by segmental units and describe extraction and use of suprasegmental information

Low HRV entropy is strongly associated with myocardial infarction

Heart rate variability (HRV) is a marker of autonomous activity in the heart. An important application of HRV measures is the stratification of mortality risk after myocardial infarction. Our hypothesis is that the information entropy of HRV, a non-linear approach, is a suitable measure for this assessment. As a first step, to evaluate the effect of myocardial infarction on the entropy, we compared the entropy to standard HRV parameters. The entropy was estimated by compressing the tachogram with Bzip2. For univariate comparison, statistical tests were used. Multivariate analysis was carried out using automatically generated decision trees. The classification rate and the simplicity of the decision trees were the two evaluation criteria. The findings support our hypothesis. The meanNN-normalized entropy is reduced in patients with myocardial infarction with very high significance. One entropy parameter alone exceeds the discrimination strength of multivariate standards-based trees

The Submarine Volcano Eruption off El Hierro Island: Effects on the Scattering Migrant Biota and the Evolution of the Pelagic Communities

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Degradation of haloaromatic compounds

An ever increasing number of halogenated organic compounds has been produced by industry in the last few decades. These compounds are employed as biocides, for synthetic polymers, as solvents, and as synthetic intermediates. Production figures are often incomplete, and total production has frequently to be extrapolated from estimates for individual countries. Compounds of this type as a rule are highly persistent against biodegradation and belong, as "recalcitrant" chemicals, to the class of so-called xenobiotics. This term is used to characterise chemical substances which have no or limited structural analogy to natural compounds for which degradation pathways have evolved over billions of years. Xenobiotics frequently have some common features. e.g. high octanol/water partitioning coefficients and low water solubility which makes for a high accumulation ratio in the biosphere (bioaccumulation potential). Recalcitrant compounds therefore are found accumulated in mammals, especially in fat tissue, animal milk supplies and also in human milk. Highly sophisticated analytical techniques have been developed for the detection of organochlorines at the trace and ultratrace level

ISADORA - a Speech Modelling Network Based on Hidden Markov Models

In this paper we present the ISADORA system which provides highly flexible speech recognition based on HMM technology together with an hierarchical representation of speech units. Markov model topologies, subword unit inventories, regular grammars expressed in finite-state or phrase structure style, and even the analysis tasks themselves are explicitly represented by the nodes of a large speech unit network. Thus, nothing that can be "said in the language of Markov models" needs to be hard-wired in the program code. In contrast to traditional compiled network recognizers, units, grammars, and tasks may be created or modified at analysis time, and the outcome of the decoding process is a structured symbolic description of the sensory input. Our architecture has proven extremely useful in prototyping new kinds of subword units. Besides generalized triphones and context-freezing units, a new subword speech unit for automatic speech recognition has been implemented. The so-called polyphone..

Flexible Steuerung eines sprachverstehenden Systems mit Hilfe mehrkomponentiger Bewertungen

Sagerer G, Kummert F, Schukat-Talamazzini G. Flexible Steuerung eines sprachverstehenden Systems mit Hilfe mehrkomponentiger Bewertungen. In: Paulus E, ed. Mustererkennung 1987: 9. DAGM-Symposium, Braunschweig, September/Oktober 1987 ; Proceedings. Informatik-Fachberichte. Vol 149. Berlin [u.a.]: Springer; 1987: 123-127

Speech Recognition Using Semantic Hidden Markov Networks

Fink GA, Kummert F, Sagerer G, Schukat-Talamazzini EG. Speech Recognition Using Semantic Hidden Markov Networks. In: Proc. European Conf. on Speech Communication and Technology. Vol 3. Berlin; 1993: 1571-1574.Semantic Hidden Markov Networks (SHMNs) were introduced as a new technique of interfacing between linguistic analysis and word recognition in speech understanding systems. The main difference between SHMNs and the use of traditional language models is that SHMNs always refer to a linguistic concept and impose the linguistic structure as closely as possible on its acoustic counterpart — a hierarchically structured HMM. Normally the result of decoding a HMM is merely the sequence of best fitting elementary acoustic concepts, e.g. phonemes or words. Taking into account the structure of the recognition task a structured instance can be computed. This complex acoustic instance can easily be transformed into a linguistic instance by a recursive computation but without any searching. In this paper we present an algorithm for generating linguistic instances from word recognition results based on SHMNs. Additionally, we present recognition results obtained when evaluating a set of SHMNs for the task domain of train schedule information

Ein Lexikon für ein natürlich-sprachliches Dialogsystem

Unglaub J, Ehrlich U, Niemann H, Sagerer G, Schukat-Talamazzini EG. Ein Lexikon für ein natürlich-sprachliches Dialogsystem. In: Jahrestagung der Gesellschaft für Linguistische Datenverarbeitung. Bonn; 1990