1. Articles in category: Segmentation

    73-96 of 578 « 1 2 3 4 5 6 7 ... 22 23 24 »
    1. Natural Language Processing (NLP) Market: Drivers And Restraints 2015 - 2021

      Submitted by aarti_PMR . Natural Language Processing (NLP) is a field of computer science and artificial intelligence that is concerned with the interaction between computer and human language. Natural language processing basically works as a bridge between human and machines. It enhances the interaction by analyzing the written and spoken languages and the pattern accordingly.

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    2. Systems and methods for natural language generation

      A method includes receiving a corpus comprising a set of pre-segmented texts. The method further includes creating a plurality of modified pre-segmented texts for the set of pre-segmented texts by extracting a set of semantic terms for each pre-segmented text within the set of pre-segmented texts and applying at least one domain tag for each pre-segmented text within the set of pre-segmented texts. The method further includes clustering the plurality of modified pre-segmented texts into one or more conceptual units, wherein each of the one or more conceptual units is associated with one or more templates, wherein each of the ...

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    3. Worldwide Natural Language Processing (NLP) Market: Drivers, Challenges and Industry Key Events 2015 to 2021

      Worldwide Natural Language Processing (NLP) Market: Drivers, Challenges and Industry Key Events 2015 to 2021 Natural language processing is segmented on the basis of type, technology, service, deployment model, vertical and region. New York, NY -- ( SBWIRE ) -- 08/11/2016 -- Natural Language processing (NLP) is a field of computer science and artificial intelligence that is concerned with the interaction between computer and human language.

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    4. Content presentation method, content presentation device, and program

      A content presenting method of the present disclosure includes: a history collecting step of collecting a viewing history of a user; a determining step of analyzing the viewing history to determine an active time segment in which an output section is in a state of being viewed; a data collecting step of collecting meta data assigned to a viewed content; an analyzing step of analyzing the meta data to extract a word representing the content; a profile generating step of generating, for each active time segment, a user profile based on the extracted word; a calculation step of calculating an ...

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    5. Method and device for acoustic language model training

      A method and a device for training an acoustic language model, include: conducting word segmentation for training samples in a training corpus using an initial language model containing no word class labels, to obtain initial word segmentation data containing no word class labels; performing word class replacement for the initial word segmentation data containing no word class labels, to obtain first word segmentation data containing word class labels; using the first word segmentation data containing word class labels to train a first language model containing word class labels; using the first language model containing word class labels to conduct word ...

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    6. SegmentAnt 1.1.0 (Freeware)

      SegmentAnt 1.1.0 (Freeware)

      changelog Freeware Seamlessly segment Chinese and Japanese texts into separate tokens that you can use in text-to-speech or linguistic analysis projects Generally speaking, there are very few situations when the computational processing of written text into separate constitute tokens is not performed in the first place. SegmentAnt is a specialized application designed to help you segment text content that is written in Chinese and Japanese.

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    7. Neural Word Segmentation Learning for Chinese. (arXiv:1606.04300v1 [cs.CL])

      Most previous approaches to Chinese word segmentation formalize this problem as a character-based sequence labeling task so that only contextual information within fixed sized local windows and simple interactions between adjacent tags can be captured. In this paper, we propose a novel neural framework which thoroughly eliminates context windows and can utilize complete segmentation history.

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    8. Graph-Community Detection for Cross-Document Topic Segment Relationship Identification. (arXiv:1606.04081v1 [cs.CL])

      In this paper we propose a graph-community detection approach to identify cross-document relationships at the topic segment level. Given a set of related documents, we automatically find these relationships by clustering segments with similar content (topics). In this context, we study how different weighting mechanisms influence the discovery of word communities that relate to the different topics found in the documents.

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    9. Natural Language Processing (NLP) Market: Latest Innovations, Drivers, Restraints, Challenges and Forecast 2015 - 2021

      Natural Language Processing (NLP) Market: Latest Innovations, Drivers, Restraints, Challenges and Forecast 2015 - 2021 Persistence Market Research PVT. LTD. Natural Language processing (NLP) is a field of computer science and artificial intelligence that is concerned with the interaction between computer and human language. Natural language processing basically works as a bridge between human and machines.

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    10. Pointing-based display interaction

      A method includes receiving and segmenting a first sequence of three-dimensional (3D) maps over time of at least a part of a body of a user of a computerized system in order to extract 3D coordinates of a first point and a second point of the user, the 3D maps indicating a motion of the second point with respect to a display coupled to the computerized system. A line segment that intersects the first point and the second point is calculated, and a target point is identified where the line segment intersects the display. An interactive item presented on the ...

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    11. Sub-vector Extraction and Cascade Post-Processing for Speaker Verification Using MLLR Super-vectors. (arXiv:1605.03724v1 [cs.SD])

      In this paper, we propose a speaker-verification system based on maximum likelihood linear regression (MLLR) super-vectors, for which speakers are characterized by m-vectors. These vectors are obtained by a uniform segmentation of the speaker MLLR super-vector using an overlapped sliding window.

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      Mentions: Mllr
    12. Recipe text and image extraction

      Embodiments process a recipe from structured data to extract recipe text and select an image representative of the recipe. Recipes in structured data are retrieved and sequenced into segments to facilitate further processing. A recipe parser generates features corresponding to the segments. These generated features are inputs to a recipe model to classify the segments into components. This recipe model is trained according to classified training recipes. The trained model may then determine classifications for segments of the recipe. The classified recipe text is used to select the representative image for the recipe. To select this image, candidate images for ...

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    13. Resolving Language and Vision Ambiguities Together: Joint Segmentation & Prepositional Attachment Resolution in Captioned Scenes. (arXiv:1604.02125v1 [cs.CV])

      We present an approach to simultaneously perform semantic segmentation and prepositional phrase attachment resolution for captioned images. The motivation for this work comes from the fact that some ambiguities in language simply cannot be resolved without simultaneously reasoning about an associated image.

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    14. A Character-level Decoder without Explicit Segmentation for Neural Machine Translation. (arXiv:1603.06147v1 [cs.CL])

      The existing machine translation systems, whether phrase-based or neural, have relied almost exclusively on word-level modelling with explicit segmentation. In this paper, we ask a fundamental question: can neural machine translation generate a character sequence without any explicit segmentation?

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    15. Unsupervised word segmentation and lexicon discovery using acoustic word embeddings. (arXiv:1603.02845v1 [cs.CL])

      In settings where only unlabelled speech data is available, speech technology needs to be developed without transcriptions, pronunciation dictionaries, or language modelling text. A similar problem is faced when modelling infant language acquisition. In these cases, categorical linguistic structure needs to be discovered directly from speech audio. We present a novel unsupervised Bayesian model that segments unlabelled speech and clusters the segments into hypothesized word groupings.

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    16. Segmental Recurrent Neural Networks for End-to-end Speech Recognition. (arXiv:1603.00223v1 [cs.CL])

      We study the segmental recurrent neural network for end-to-end acoustic modelling. This model connects the segmental conditional random field (CRF) with a recurrent neural network (RNN) used for feature extraction. Compared to most previous CRF-based acoustic models, it does not rely on an external system to provide features or segmentation boundaries.

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    17. Speculation Detection for Chinese Clinical Notes: Impacts of Word Segmentation and Embedding Models.

      Speculation Detection for Chinese Clinical Notes: Impacts of Word Segmentation and Embedding Models.

      Speculation Detection for Chinese Clinical Notes: Impacts of Word Segmentation and Embedding Models.

      J Biomed Inform. 2016 Feb 25;

      Authors: Zhang S, Kang T, Zhang X, Wen D, Elhadad N, Lei J

      Abstract Speculations represent uncertainty towards certain facts. In clinical texts, identifying speculations is a critical step of natural language processing (NLP).

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      Mentions: NLP Elsevier Inc.
    18. Device and method for term set expansion based on semantic similarity

      A receiving unit (101) receives a seed string. A search unit (102) searches snippets of documents containing the seed string. A segment acquisition unit (103) obtains segments by partitioning the snippets using a segment partition string. A segment component acquisition unit (104) obtains segment components by partitioning the segments using a segment component partition string. A segment score computation unit (105) calculates a segment score for a segment based on the standard deviation of the lengths of the segment components. A segment component score computation unit (106) calculates a segment component score for a segment component based on the segment ...

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    19. Systems and methods for performing multi-modal video datastream segmentation

      Systems and methods are described that can provide users with personalized video content feeds. In several embodiments, a multi-modal segmentation process is utilized that relies upon cues derived from video, audio and/or text data present in a video data stream. In a number of embodiments, video streams from a variety of sources are segmented. Links are identified between video segments and between video segments and online articles containing additional information relevant to the video segments. The additional information obtained by linking a video segment to an additional source of data can be utilized in the generation of personalized playlists ...

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    73-96 of 578 « 1 2 3 4 5 6 7 ... 22 23 24 »
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