Abstract: The invention relates to a method, a computer program product and a computer system for structuring an unstructured text by making use of statistical models trained on annotated training data. Each section of text in which the text is segmented is further assigned to a topic which is associated to a set of labels. The statistical models for the segmentation of the text and for the assignment of a topic and its associated labels to a section of text explicitly accounts for: correlations between a section of text and a topic, a topic transition between sections, a topic position within the document and a (topic-dependent) section length. Hence structural information of the training data is exploited in order to perform segmentation and annotation of unknown text.

Abstract: The present invention relates to a method, a text segmentation system and a computer program product for clustering of text into text clusters representing a distinct semantic meaning. The text clustering method identifies text portions and assigns text portions to different clusters in such a way that each text cluster refers to one or several semantic topics. The clustering method incorporates an optimization procedure based on a re-clustering procedure evaluating a target function being indicative of the correlation between a text unit and a cluster. The text clustering method makes use of a text emission model and a cluster transition model and makes further use of various smoothing techniques.

Abstract: A connection of the stabilizer parts of a two-part stabilizer to an actuator is usually performed in a positive-locking manner, as a result of which an additional axial securing and hydraulic sealing toward the outside become necessary. To simplify the design and the manufacturing process, it is provided that the teeth between the outer rotary part (4) and the second stabilizer part (2) be made clearance-free and welded together by a circumferential weld seam (18), wherein the seam area is preheated to a temperature of 350° C. and subsequently cooled to a martensite content of 30% in the microstructure.

Abstract: The invention relates to a method, an apparatus, a Graphical User Interface and a computer program product for transforming speech to text. In a speech recognition step (100) a text is provided to which an automatic text modification based on text modification rules is applied (102). Text portions to which the modification applies, are highlighted in the text (106) and at least one suggestion for the modification is displayed to a user (110), being enabled to select one of the suggestions and therefore having control over the automatic text modification process (112). For example the rules identify text portions relating to ambiguous speech or missing text formatting characters that might have been misinterpreted in the speech recognition step.

Abstract: The invention relates to a speech recognition system and a method of calculating iteration values for free parameters ??ortho(n) of a maximum-entropy speech model MESM with the aid of the generalized-iterative scaling training algorithm in a computer-supported speech recognition system in accordance with the formula ??ortho(n+1)=G(??ortho(n), m?ortho, . . . ), where n is an iteration parameter, G a mathematical function, ? an attribute in the MESM and m?ortho a desired orthogonalized boundary value in the MESM for the attribute ?. It is an object of the invention to further develop the system and method so that they make a fast computation of the free parameters ? possible without a change of the original training object. According to the invention this object is achieved in that the desired orthogonalized boundary value m?ortho is calculated by a linear combination of the desired boundary value m? with desired boundary values m? from attributes ? that have a larger range than the attribute ?.

Abstract: A connection of the stabilizer parts of a two-part stabilizer to an actuator is usually performed in a positive-locking manner, as a result of which an additional axial securing and hydraulic sealing toward the outside become necessary. To simplify the design and the manufacturing process, it is provided that the teeth between the outer rotary part (4) and the second stabilizer part (2) be made clearance-free and welded together by a circumferential weld seam (18), wherein the seam area is preheated to a temperature of 350° C. and subsequently cooled to a martensite content of 30% in the microstructure.

Abstract: The invention concerns antibodies to special forms of enzymatically non-active precursors of prostate specific antigen (PSA), their production, their use in immunoassays for determination of [−5, −6, −7] proPSA and the use of measured values from these assays for improved diagnostics in the field of prostatic carcinoma.

Abstract: The invention concerns a method for the purification of a target substance from a biological sample by immobilizing the target substance on a solid phase by means of a high affinity binding pair and subsequently eluting it by adding a partner of the binding pair in a free form. In addition reagent kits for carrying out the method are disclosed.

Abstract: The invention relates to a method of setting a free parameter 1 λ α ortho

Abstract: The invention relates to a speech recognition system and a method of calculating iteration values for free parameters &lgr;&agr; of the maximum entropy speech model. In the state of the art it is known that these free parameters &lgr;&agr; can be approximated cyclically and iteratively, for example, using a GIS training algorithm. Cyclically in this case is understood to mean that for each iteration step n a cyclically predefined attribute group Ai(n) of the speech model is evaluated in order to calculate the n+1 iteration value for the free parameters. An attribute group Ai(n) with such a rigid cyclical assignment is not always the best solution, however, for ensuring the fastest and most effective convergence of the GIS training algorithm in a given situation.

Abstract: The invention relates to a speech recognition system and a method of calculating iteration values for free parameters &lgr;&agr;ortho(n) of a maximum-entropy speech model MESM with the aid of the generalized-iterative scaling training algorithm in a computer-supported speech recognition system in accordance with the formula

Abstract: A device for recycling a liquid that has collected on the inner wall of a tube through which a gas stream flows includes (1) a tube having an inner wall and (2) capillaries on the inner wall of the tube that project into the gas stream.

Abstract: The invention concerns an immunological process for the determination of prostate-specific antigen (PSA), particularly for the determination of free PSA, the total concentration of PSA and the concentration of PSA-serpin complexes by incubation of the sample with at least one antibody specifically binding to free PSA but not to complex PSA. The process is characterized in that especially before the determination of the total PSA concentration a nucleophile containing amine is added to the sample. Furthermore, the invention concerns the use of amine-containing nucleophiles for the production of free PSA as well as a procedure for preparing free PSA from complex PSA by incubation of a sample containing complex PSA with a nucleophile containing amine.

Abstract: The invention relates to a method of generating a maximum entropy speech model for a speech recognition system.

Abstract: Language models which take into account the probabilities of word sequences are used in speech recognition, in particular in the recognition of fluently spoken language with a wide vocabulary, in order to increase the recognition reliability. These models are obtained from comparatively large quantities of text and accordingly represent values which were averaged over several texts. This means, however, that the language model is not well adapted to peculiarities of a special text. To achieve such an adaptation of a given language model to a special text on the basis of only a short text fragment, according to the invention, it is suggested that first the unigram language model is adapted with the short text and, in dependence thereon, the M-gram language model is subsequently adapted. A method is described for adapting the unigram language model values which automatically carries out a subdivision of the words into semantic classes.