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    Zero-search, zero-memory vector quantization
    41.
    发明授权
    Zero-search, zero-memory vector quantization 有权
    零搜索，零存储矢量量化

    公开(公告)号：US08185390B2

    公开(公告)日：2012-05-22

    申请号：US12429122

    申请日：2009-04-23

    Applicant: Harry Printz

    Inventor： Harry Printz

    IPC: G10L15/00

    CPC classification number: H03M7/3082 ,  G06Q30/02 ,  G10L15/26 ,  G10L17/00 ,  G10L19/00 ,  G10L25/24 ,  H04N19/94

    Abstract: The invention comprises a method for lossy data compression, akin to vector quantization, in which there is no explicit codebook and no search, i.e. the codebook memory and associated search computation are eliminated. Some memory and computation are still required, but these are dramatically reduced, compared to systems that do not exploit this method. For this reason, both the memory and computation requirements of the method are exponentially smaller than comparable methods that do not exploit the invention. Because there is no explicit codebook to be stored or searched, no such codebook need be generated either. This makes the method well suited to adaptive coding schemes, where the compression system adapts to the statistics of the data presented for processing: both the complexity of the algorithm executed for adaptation, and the amount of data transmitted to synchronize the sender and receiver, are exponentially smaller than comparable existing methods.

    Abstract translation: 本发明包括一种类似向量量化的有损数据压缩的方法，其中没有显式的码本而没有搜索，即消除了码本存储器和相关的搜索计算。 仍然需要一些内存和计算，但与不利用此方法的系统相比，这些内存和计算仍然需要大大减少。 因此，该方法的存储器和计算要求都比指数地小于不利用本发明的可比方法。 因为没有明确的代码簿要存储或搜索，所以也不需要生成这样的代码簿。 这使得该方法非常适合于自适应编码方案，其中压缩系统适应所呈现的用于处理的数据的统计：为适应而执行的算法的复杂度以及发送以同步发送方和接收方的数据量是 指数地小于可比较的现有方法。

    Efficient empirical determination, computation, and use of acoustic confusability measures
    45.
    发明授权
    Efficient empirical determination, computation, and use of acoustic confusability measures 有权

    公开(公告)号：US10748527B2

    公开(公告)日：2020-08-18

    申请号：US16158900

    申请日：2018-10-12

    Applicant: Promptu Systems Corporation

    Inventor： Harry Printz ,  Naren Chittar

    IPC: G10L15/187 ,  G06F16/9535 ,  G06Q30/02 ,  G10L17/26 ,  G10L15/18 ,  G10L15/22 ,  G10L15/02 ,  G10L15/14 ,  G06F16/95

    Abstract: Efficient empirical determination, computation, and use of an acoustic confusability measure comprises: (1) an empirically derived acoustic confusability measure, comprising a means for determining the acoustic confusability between any two textual phrases in a given language, where the measure of acoustic confusability is empirically derived from examples of the application of a specific speech recognition technology, where the procedure does not require access to the internal computational models of the speech recognition technology, and does not depend upon any particular internal structure or modeling technique, and where the procedure is based upon iterative improvement from an initial estimate; (2) techniques for efficient computation of empirically derived acoustic confusability measure, comprising means for efficient application of an acoustic confusability score, allowing practical application to very large-scale problems; and (3) a method for using acoustic confusability measures to make principled choices about which specific phrases to make recognizable by a speech recognition application.

    Efficient empirical computation and utilization of acoustic confusability
    48.
    发明授权
    Efficient empirical computation and utilization of acoustic confusability 有权

    公开(公告)号：US09626965B2

    公开(公告)日：2017-04-18

    申请号：US14574314

    申请日：2014-12-17

    Applicant: PROMPTU SYSTEMS CORPORATION

    Inventor： Harry Printz ,  Naren Chittar

    IPC: G10L15/12 ,  G10L15/187 ,  G10L15/22 ,  G06Q30/02 ,  G10L17/26 ,  G10L15/18 ,  G06F17/30

    CPC classification number: G10L15/187 ,  G06F17/30861 ,  G06F17/30867 ,  G06Q30/02 ,  G10L15/02 ,  G10L15/142 ,  G10L15/18 ,  G10L15/22 ,  G10L17/26 ,  G10L2015/025

    Abstract: Efficient empirical determination, computation, and use of an acoustic confusability measure comprises: (1) an empirically derived acoustic confusability measure, comprising a means for determining the acoustic confusability between any two textual phrases in a given language, where the measure of acoustic confusability is empirically derived from examples of the application of a specific speech recognition technology, where the procedure does not require access to the internal computational models of the speech recognition technology, and does not depend upon any particular internal structure or modeling technique, and where the procedure is based upon iterative improvement from an initial estimate; (2) techniques for efficient computation of empirically derived acoustic confusability measure, comprising means for efficient application of an acoustic confusability score, allowing practical application to very large-scale problems; and (3) a method for using acoustic confusability measures to make principled choices about which specific phrases to make recognizable by a speech recognition application.

    Method and apparatus for generation and augmentation of search terms from external and internal sources
    50.
    发明授权
    Method and apparatus for generation and augmentation of search terms from external and internal sources 有权
    从外部和内部来源生成和增加搜索词的方法和装置

    公开(公告)号：US08862596B2

    公开(公告)日：2014-10-14

    申请号：US13667446

    申请日：2012-11-02

    Applicant: Promptu Systems Corporation

    Inventor： Joseph Bruce Stampleman ,  Harry Printz

    IPC: G06F17/30 ,  G10L17/26 ,  G06Q30/02

    CPC classification number: G10L15/187 ,  G06F17/30861 ,  G06F17/30867 ,  G06Q30/02 ,  G10L15/02 ,  G10L15/142 ,  G10L15/18 ,  G10L15/22 ,  G10L17/26 ,  G10L2015/025

    Abstract: A method and apparatus to identify names, personalities, titles, and topics that are present in a repository and to identify names, personalities, titles, and topics that are not present in the repository, uses information from external data sources, notably the text used in non-speech, text-based searches, to expand the search terms. The expansion takes place in two forms: (1) finding plausible linguistic variants of existing search terms that are already comprehended in the repository, but that are present under slightly different names; and (2) expanding the existing search term list with items that should be there by virtue of their currency in popular culture, but which for whatever reason have not yet been reflected with content items in the repository.

    Abstract translation: 识别存储库中存在的名称，个性，标题和主题以及识别存储库中不存在的名称，个性，标题和主题的方法和装置使用来自外部数据源的信息，特别是所使用的文本 在非语音，基于文本的搜索中，扩展搜索词。 扩展有两种形式：（1）找到已经在知识库中理解的现有搜索词的合理语言变体，但存在于稍微不同的名称下; 和（2）扩大现有的搜索项目列表，其项目应该是以流通文化中的货币存在的，但由于任何原因，还没有反映在存储库中的内容项目。

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