1. Articles in category: Segmentation

    49-72 of 545 « 1 2 3 4 5 6 ... 21 22 23 »
    1. 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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    2. 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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    3. 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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    4. 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
    5. 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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    6. 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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    7. 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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    8. 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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    9. 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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    10. 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.
    11. 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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    12. 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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    13. Selection models of language production support informed text partitioning: an intuitive and practical, bag-of-phrases framework for text analysis. (arXiv:1601.07969v1 [cs.CL])

      The task of text segmentation, or 'chunking,' may occur at many levels in text analysis, depending on whether it is most beneficial to break it down by paragraphs of a book, sentences of a paragraph, etc. Here, we focus on a fine-grained segmentation task, which we refer to as text partitioning, where we apply methodologies to segment sentences or clauses into phrases, or lexical constructions of one or more words.

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    14. Automatic collection of speaker name pronunciations

      An audio stream is segmented into a plurality of time segments using speaker segmentation and recognition (SSR), with each time segment corresponding to the speaker's name, producing an SSR transcript. The audio stream is transcribed into a plurality of word regions using automatic speech recognition (ASR), with each of the word regions having a measure of the confidence in the accuracy of the translation, producing an ASR transcript. Word regions with a relatively low confidence in the accuracy of the translation are identified. The low confidence regions are filtered using named entity recognition (NER) rules to identify low confidence ...

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      Mentions: ASR NER
    15. Voice synthesizer

      A candidate voice segment sequence generator 1 generates candidate voice segment sequences 102 for an input language information sequence 101 by using DB voice segments 105 in a voice segment database 4. An output voice segment sequence determinator 2 calculates a degree of match between the input language information sequence 101 and each of the candidate voice segment sequences 102 by using a parameter 107 showing a value according to a cooccurrence criterion 106 for cooccurrence between the input language information sequence 101 and a sound parameter showing the attribute of each of a plurality of candidate voice segments in ...

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    16. Natural Language Processing (NLP) Market - Pmr's Analysis of Global Key Trends, Drivers, and Restraints from Supply and Demand Perspectives

      Persistence Market Research Pvt. Ltd is released new forthcoming report on title "Natural Language Processing (NLP) Market: Global Industry Analysis and Forecast 2015 - 2021". New York, NY -- (SBWIRE) -- 12/08/2015 -- Natural Language processing (NLP) is a ...

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    17. Temporal topic segmentation and keyword selection for text visualization

      Visualizing content change of a data collection over time. A topic may be split into multiple linear, non-overlapping sub-topics along a timeline by satisfying a diverse set of semantic, temporal, and visualization constraints simultaneously. For each derived sub-topic, a set of representative keywords may be automatically selected to summarize the main content of the sub-topic.

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    18. Segmental Recurrent Neural Networks. (arXiv:1511.06018v1 [cs.CL])

      We introduce segmental recurrent neural networks (SRNNs) which define, given an input sequence, a joint probability distribution over segmentations of the input and labelings of the segments. Representations of the input segments (i.e., contiguous subsequences of the input) are computed by encoding their constituent tokens using bidirectional recurrent neural nets, and these "segment embeddings" are used to define compatibility scores with output labels.

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    19. Method and apparatus for generating video descriptions

      Provided in some embodiments is a computer implemented method that includes receiving time-aligned script data including dialogue words of a script and timecodes corresponding to the dialogue words, identifying gaps between dialogue words for the insertion of video description content, wherein the gaps are identified based on the duration of pauses between timecodes of adjacent dialogue words, aligning segments of video description content with corresponding gaps in dialogue, wherein the video description content for the segments is derived from corresponding script elements of the script; and generating a script document including the aligned segments of video description content.

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    20. Context-based document unit recommendation for sensemaking tasks

      Techniques for locating information in a document relevant to an interest of a user are provided. Information defined by the user of a document browser is collected. A context model is generated using the collected information. A document selected by the user is obtained. The document is divided into one or more segments. A relevance value is computed for each of the one or more segments by comparing each of the one or more segments to the context model. The relevance value represents a relationship to an interest of the user. Each of the one or more segments with the ...

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    21. Combine CRF and MMSEG to Boost Chinese Word Segmentation in Social Media. (arXiv:1510.07099v1 [cs.CL])

      In this paper, we propose a joint algorithm for the word segmentation on Chinese social media. Previous work mainly focus on word segmentation for plain Chinese text, in order to develop a Chinese social media processing tool, we need to take the main features of social media into account, whose grammatical structure is not rigorous, and the tendency of using colloquial and Internet terms makes the existing Chinese-processing tools inefficient to obtain good performance on social media.

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    49-72 of 545 « 1 2 3 4 5 6 ... 21 22 23 »
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