Abstract: The invention relates to a method, a computer program product, a segmentation system and a user interface for structuring an unstructured text by making use of statistical models trained on annotated training data. The method performs text segmentation into text sections and assigns labels to text sections as section headings. The performed segmentation and assignment is provided to a user for general review. Additionally, alternative segmentations and label assignments are provided to the user being capable to select alternative segmentations and alternative labels as well as to enter a user defined segmentation and user defined label. In response to the modifications introduced by the user, a plurality of different actions are initiated incorporating the re-segmentation and re-labeling of successive parts of the document or the entire document.

Abstract: The invention relates to an assistance system (1, 25) for providing support in situation-dependent planning and/or guidance tasks of a controlled system (2), comprising a state detection unit (3) for detecting at least one state (5, 5a) of the controlled system (2), an acoustic receiving unit (9, 27), which is designed to receive acoustic voice signals of voice communication (24) between at least two persons (21, 22), and a voice processing unit (7), which is designed to detect voice information (10) regarding the controlled system (2) from the received acoustic voice signals, wherein the state detection unit (3) is designed to adapt the detected state (5) and/or a predicted state (5a) of the controlled system (2) that can be derived from the current state, according to the detected voice information (10).

Abstract: The invention relates to a method, a computer program product, a segmentation system and a user interface for structuring an unstructured text by making use of statistical models trained on annotated training data. The method performs text segmentation into text sections and assigns labels to text sections as section headings. The performed segmentation and assignment is provided to a user for general review. Additionally, alternative segmentations and label assignments are provided to the user being capable to select alternative segmentations and alternative labels as well as to enter a user defined segmentation and user defined label.

Abstract: The invention relates to a method, a computer program product, a segmentation system and a user interface for structuring an unstructured text by making use of statistical models trained on annotated training data. The method performs text segmentation into text sections and assigns labels to text sections as section headings. The performed segmentation and assignment is provided to a user for general review. Additionally, alternative segmentations and label assignments are provided to the user being capable to select alternative segmentations and alternative labels as well as to enter a user defined segmentation and user defined label. In response to the modifications introduced by the user, a plurality of different actions are initiated incorporating the re-segmentation and re-labeling of successive parts of the document or the entire document.

Abstract: The invention relates to a method, a computer program product, a segmentation system and a user interface for structuring an unstructured text by making use of statistical models trained on annotated training data. The method performs text segmentation into text sections and assigns labels to text sections as section headings. The performed segmentation and assignment is provided to a user for general review. Additionally, alternative segmentations and label assignments are provided to the user being capable to select alternative segmentations and alternative labels as well as to enter a user defined segmentation and user defined label. In response to the modifications introduced by the user, a plurality of different actions are initiated incorporating the re-segmentation and re-labeling of successive parts of the document or the entire document.

Abstract: The invention relates to a method, a computer program product, a segmentation system and a user interface for structuring an unstructured text by making use of statistical models trained on annotated training data. The method performs text segmentation into text sections and assigns labels to text sections as section headings. The performed segmentation and assignment is provided to a user for general review. Additionally, alternative segmentations and label assignments are provided to the user being capable to select alternative segmentations and alternative labels as well as to enter a user defined segmentation and user defined label. In response to the modifications introduced by the user, a plurality of different actions are initiated incorporating the re-segmentation and re-labeling of successive parts of the document or the entire document.

Abstract: The invention relates to a method, a computer program product, a segmentation system and a user interface for structuring an unstructured text by making use of statistical models trained on annotated training data. The method performs text segmentation into text sections and assigns labels to text sections as section headings. The performed segmentation and assignment is provided to a user for general review. Additionally, alternative segmentations and label assignments are provided to the user being capable to select alternative segmentations and alternative labels as well as to enter a user defined segmentation and user defined label. In response to the modifications introduced by the user, a plurality of different actions are initiated incorporating the re-segmentation and re-labelling of successive parts of the document or the entire document.

Abstract: The invention relates to a method, a computer program product, a segmentation system and a user interface for structuring an unstructured text by making use of statistical models trained on annotated training data. The method performs text segmentation into text sections and assigns labels to text sections as section headings. The performed segmentation and assignment is provided to a user for general review. Additionally, alternative segmentations and label assignments are provided to the user being capable to select alternative segmentations and alternative labels as well as to enter a user defined segmentation and user defined label. In response to the modifications introduced by the user, a plurality of different actions are initiated incorporating the re-segmentation and re-labeling of successive parts of the document or the entire document.

Abstract: The present invention relates to a method, a computer system and a computer program product for speech recognition and/or text formatting by making use of topic specific statistical models. A text document which may be obtained from a first speech recognition pass is subject to segmentation and to an assignment of topic specific models for each obtained section. Each model of the set of models provides statistic information about language model probabilities, about text processing or formatting rules, as e.g. the interpretation of commands for punctuation, formatting, text highlighting or of ambiguous text portions requiring specific formatting, as well as a specific vocabulary being characteristic for each section of the recognized text. Furthermore, other properties of a speech recognition and/or formatting system (such as e.g. settings for the speaking rate) may be encoded in the statistical models. The models themselves are generated on the basis of annotated training data and/or by manual coding.

Abstract: The invention describes a method for storing broadcast contents and a broadcast content storage system. A plurality of content categories (KAT1, KAT2) is pre-defined, each of which is defined or described by at least one content descriptor (OB 1, OB2). Broadcast contents transmitted over at least one broadcast transmission channel are received, preferably continually, or over pre-defined lengths of time. Received broadcast contents, which are described by a content descriptor (OB1, OB2), are automatically assigned to the content category (KAT1, KAT2) defined or described by the corresponding content descriptor (OB1, OB2). The broadcast contents assigned to a content category (KAT1, KAT2) and the assignments of the broadcast contents to the corresponding content categories (KAT1, KAT2) are automatically stored.

Abstract: The invention relates to a method, a computer program product, a segmentation system and a user interface for structuring an unstructured text by making use of statistical models trained on annotated training data. The method performs text segmentation into text sections and assigns labels to text sections as section headings. The performed segmentation and assignment is provided to a user for general review. Additionally, alternative segmentations and label assignments are provided to the user being capable to select alternative segmentations and alternative labels as well as to enter a user defined segmentation and user defined label. In response to the modifications introduced by the user, a plurality of different actions are initiated incorporating the re-segmentation and re-labelling of successive parts of the document or the entire document.

Abstract: The present invention relates to a method, a computer system and a computer program product for speech recognition and/or text formatting by making use of topic specific statistical models. A text document which may be obtained from a first speech recognition pass is subject to segmentation and to an assignment of topic specific models for each obtained section. Each model of the set of models provides statistic information about language model probabilities, about text processing or formatting rules, as e.g. the interpretation of commands for punctuation, formatting, text highlighting or of ambiguous text portions requiring specific formatting, as well as a specific vocabulary being characteristic for each section of the recognized text. Furthermore, other properties of a speech recognition and/or formatting system (such as e.g. settings for the speaking rate) may be encoded in the statistical models. The models themselves are generated on the basis of annotated training data and/or by manual coding.

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 invention describes a method for controlling a media content processing device (1). It is thereby determined whether a media content (VI) to be processed is described by a pre-defined content descriptor (CD1, CD2) from a multitude of pre-defined content descriptors (CD1, CD2). A device control parameter (P11, P12, P21, P22) is automatically adjusted based on the content descriptor (CD1, CD2) which describes the media content (VI) to be processed. Then, the media content processing device (1) is automatically controlled, based on the device control parameter (P11, P12, P21, P22).

Abstract: The invention relates to a method for recording content on a record medium (2) that contains a desired content descriptor (3), comprising the steps of reading said desired content descriptor (3) from said record medium (2), scanning the content (10, 12) of at least one multimedia source (6, 7) for desired content that matches said desired content descriptor (3), and recording said desired content on said record medium (3). Said record medium (2) is preferably a Digital Versatile Disc (DVD), said desired content descriptor (3) is preferably a keyword contained in a blank of said DVD, and said at least one multimedia source (6, 7) is preferably a television receiver. The DVD with the keyword contained therein thus triggers the recording of content from the television receiver that matches said keyword on said DVD. The invention further relates to a computer program product, a device and a record medium.

Abstract: The invention relates to a method and a device for the transcription of spoken and written utterances. To this end, the utterances undergo speech or text recognition, and the recognition result (ME) is combined with a manually created transcription (MT) of the utterances in order to obtain the transcription. The additional information rendered usable by the combination as a result of the recognition result (ME) enables the transcriber to work relatively roughly and therefore quickly on the manual transcription. When using a keyboard (25), he can, for example, restrict himself to hitting the keys of only one row and/or can omit some keystrokes completely. In addition, the manual transcribing can also be accelerated by the suggestion of continuations (31) to the text input so far (30), which continuations are anticipated by virtue of the recognition result (ME).

Abstract: A small vocabulary pattern recognition system is used for recognizing a sequence of words, such as a sequence of digits (e.g. telephone number) or a sequence of commands. A representation of reference words is stored in a vocabulary 132, 134. Input means 110 are used for receiving a time-sequential input pattern representative of a spoken or written word sequence. A pattern recognizer 120 comprises a word-level matching unit 130 for generating a plurality of possible sequences of words by statistically comparing the input pattern to the representations of the reference words of the vocabulary 132, 134. A cache 150 is used for storing a plurality of most recently recognized words. A sequence-level matching unit 140 selects a word sequence from the plurality of sequences of words in dependence on a statistical language model which provides a probability of a sequence of M words, M≧2. The probability depends on a frequency of occurrence of the sequence in the cache.

Abstract: The invention relates to a method of estimating probabilities of occurrence of speech vocabulary elements in a speech recognition system. By modification of the linguistic speech modeling, further alternatives for reducing the error rate and perplexity of a speech recognition system are proposed.

Abstract: The invention relates to a method of generating a language model and a method of generating an acoustic model for a speech recognition system. There is proposed to successively reduce the respective training material by training material portions in dependence on application-specific data or to extend it to obtain the respective training material for generating a language model and the acoustic model.

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.