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    METHOD AND SYSTEM OF ENVIRONMENT SENSITIVE AUTOMATIC SPEECH RECOGNITION
    2.
    发明申请
    METHOD AND SYSTEM OF ENVIRONMENT SENSITIVE AUTOMATIC SPEECH RECOGNITION 审中-公开
    环境敏感自动语音识别方法与系统

    公开(公告)号：WO2016153712A1

    公开(公告)日：2016-09-29

    申请号：PCT/US2016/019503

    申请日：2016-02-25

    Applicant: INTEL CORPORATION

    Inventor： RAVINDRAN, Binuraj ,  STEMMER, Georg ,  HOFER, Joachim

    IPC: G10L15/22 ,  G10L15/26

    CPC classification number: G10L15/20 ,  G10L15/083 ,  G10L15/285 ,  G10L25/48 ,  G10L2015/226

    Abstract: In a system of an environment-sensitive automatic speech recognition, a method includes steps for obtaining audio data including human speech, determining at least one characteristic of the environment in which the audio data was obtained, and modifying at least one parameter to be used to perform speech recognition depending on the characteristic.

    Abstract translation: 在环境敏感自动语音识别的系统中，一种方法包括获得包括人类语音的音频数据的步骤，确定获得音频数据的环境的至少一个特征，以及修改至少一个要使用的参数 根据特性进行语音识别。

    FRAME SKIPPING WITH EXTRAPOLATION AND OUTPUTS ON DEMAND NEURAL NETWORK FOR AUTOMATIC SPEECH RECOGNITION
    3.
    发明申请
    FRAME SKIPPING WITH EXTRAPOLATION AND OUTPUTS ON DEMAND NEURAL NETWORK FOR AUTOMATIC SPEECH RECOGNITION 审中-公开
    具有自动语音识别需求神经网络的外推和输出的框架

    公开(公告)号：WO2016048486A1

    公开(公告)日：2016-03-31

    申请号：PCT/US2015/045750

    申请日：2015-08-18

    Applicant: INTEL CORPORATION

    Inventor： BAUER, Josef ,  ROZEN, Piotr ,  STEMMER, Georg

    IPC: G10L15/16

    CPC classification number: G10L15/16 ,  G10L15/02 ,  G10L15/08 ,  G10L15/12

    Abstract: Techniques related to implementing neural networks for speech recognition systems are discussed. Such techniques may include implementing frame skipping with approximated skip frames and/or distances on demand such that only those outputs needed by a speech decoder are provided via the neural network or approximation techniques.

    Abstract translation: 讨论了与语音识别系统实现神经网络有关的技术。 这样的技术可以包括实现具有近似跳过帧和/或按需的距离的跳帧，使得仅通过神经网络或近似技术提供语音解码器所需的那些输出。

    IMPROVED FIXED POINT INTEGER IMPLEMENTATIONS FOR NEURAL NETWORKS
    4.
    发明申请
    IMPROVED FIXED POINT INTEGER IMPLEMENTATIONS FOR NEURAL NETWORKS 审中-公开
    改进固定点整体实现神经网络

    公开(公告)号：WO2016039651A1

    公开(公告)日：2016-03-17

    申请号：PCT/PL2014/050053

    申请日：2014-09-09

    Applicant: INTEL CORPORATION

    Inventor： ROZEN, Piotr ,  STEMMER, Georg

    IPC: G06N3/063 ,  G10L15/16

    CPC classification number: G06N3/08 ,  G06F7/483 ,  G06N3/04 ,  G06N3/063 ,  G10L15/02 ,  G10L15/16

    Abstract: Techniques related to implementing neural networks for speech recognition systems are discussed. Such techniques may include processing a node of the neural network by determining a score for the node as a product of weights and inputs such that the weights are fixed point integer values, applying a correction to the score based a correction value associated with at least one of the weights, and generating an output from the node based on the corrected score.

    Abstract translation: 讨论了与语音识别系统实现神经网络相关的技术。 这样的技术可以包括通过将节点的得分确定为权重和输入的乘积来处理神经网络的节点，使得权重是固定点整数值，对基于与至少一个相关联的校正值进行校正 的权重，并且基于校正得分从节点生成输出。

    LANGUAGE MODEL MODIFICATION FOR LOCAL SPEECH RECOGNITION SYSTEMS USING REMOTE SOURCES
    6.
    发明申请
    LANGUAGE MODEL MODIFICATION FOR LOCAL SPEECH RECOGNITION SYSTEMS USING REMOTE SOURCES 审中-公开
    使用远程来源的本地语音识别系统的语言模型修改

    公开(公告)号：WO2016209444A1

    公开(公告)日：2016-12-29

    申请号：PCT/US2016/033623

    申请日：2016-05-20

    Applicant: INTEL CORPORATION

    Inventor： DEISHER, Michael ,  STEMMER, Georg

    IPC: G10L15/22 ,  G10L15/20 ,  G10L15/02 ,  G06F15/16

    CPC classification number: G10L15/187 ,  G10L15/197 ,  G10L15/30 ,  G10L15/32

    Abstract: A language model is modified for a local speech recognition system using remote speech recognition sources. In one example, a speech utterance is received. The speech utterance is sent to at least one remote speech recognition system. Text results corresponding to the utterance are received from the remote speech recognition system. A local text result is generated using local vocabulary. The received text results and the generated text result are compared to determine words that are out of the local vocabulary and the local vocabulary is updated using the out of vocabulary words.

    Abstract translation: 对于使用远程语音识别源的本地语音识别系统，修改了语言模型。 在一个示例中，接收到讲话语音。 语音发音被发送到至少一个远程语音识别系统。 从远程语音识别系统接收到与话语相对应的文本结果。 使用本地词汇生成本地文本结果。 将接收到的文本结果和生成的文本结果进行比较，以确定不在本地词汇表中的单词，并且使用词汇单词更新本地词汇表。

    TECHNOLOGIES FOR IMPROVED KEYWORD SPOTTING
    8.
    发明申请
    TECHNOLOGIES FOR IMPROVED KEYWORD SPOTTING 审中-公开
    改进的关键字喷射技术

    公开(公告)号：WO2018057166A1

    公开(公告)日：2018-03-29

    申请号：PCT/US2017/047389

    申请日：2017-08-17

    Applicant: INTEL CORPORATION

    Inventor： MANGALATH, Praful ,  BAUER, Josef G. ,  STEMMER, Georg

    IPC: G10L15/08 ,  G10L15/22 ,  G10L25/51

    Abstract: Technologies for improved keyword spotting are disclosed. A compute device may capture speech data from a user of the compute device, and perform automatic speech recognition on the captured speech data. The automatic speech recognition algorithm is configured to both spot keywords as well as provide a full transcription of the captured speech data. The automatic speech recognition algorithm may preferentially match the keywords compared to similar words. The recognized keywords may be used to improve parsing of the transcribed speech data or to improve an assistive agent in holding a dialog with a user of the compute device.

    Abstract translation: 披露了改进的关键词识别技术。

    计算设备可以捕捉来自计算设备的用户的语音数据，并且对所捕获的语音数据执行自动语音识别。 自动语音识别算法被配置为既定位关键词以及提供所捕获的语音数据的完整转录。 自动语音识别算法可以优先匹配与类似词语相比较的关键词。 所识别的关键词可以用于改善对转录的语音数据的分析或改善助理代理与计算设备的用户保持对话。

    ADAPTIVE PHASE DIFFERENCE BASED NOISE REDUCTION FOR AUTOMATIC SPEECH RECOGNITION (ASR)
    9.
    发明申请
    ADAPTIVE PHASE DIFFERENCE BASED NOISE REDUCTION FOR AUTOMATIC SPEECH RECOGNITION (ASR) 审中-公开
    自适应语音识别自适应噪声抑制（ASR）

    公开(公告)号：WO2015041549A1

    公开(公告)日：2015-03-26

    申请号：PCT/PL2013/050022

    申请日：2013-09-17

    Applicant: INTEL CORPORATION

    Inventor： KURYLO, Lukasz ,  STEMMER, Georg

    IPC: G10L21/0272 ,  G10L21/0232 ,  H04R3/00 ,  G10L21/0216

    CPC classification number: G10K11/178 ,  G10L21/0232 ,  G10L2021/02087 ,  G10L2021/02166 ,  H04M3/568 ,  H04R3/005

    Abstract: Embodiments of a system and method for adapting a phase difference- based noise reduction system are generally described herein. In some embodiments, spatial information associated with a first and second audio signal are determined, wherein the first and second audio signals including a target audio inside a beam and noise from outside the beam. A signal-to-noise ratio (SNR) associated with the audio signals is estimated. A mapping of phase differences to gain factors is adapted for determination of attenuation factors for attenuating frequency bins associated with noise outside the beam. Spectral subtraction is performed to remove estimated noise from the single-channel signal based on a weighting that affects frequencies associated with a target signal less. Frequency dependent attenuation factors are applied to attenuate frequency bins outside the beam to produce a target signal having noise reduced.

    Abstract translation: 本文通常描述用于适配基于相位差的降噪系统的系统和方法的实施例。 在一些实施例中，确定与第一和第二音频信号相关联的空间信息，其中第一和第二音频信号包括波束内的目标音频和来自波束外的噪声。 估计与音频信号相关联的信噪比（SNR）。 相位差与增益因子的映射适用于确定用于衰减与波束外部的噪声相关联的频率仓的衰减因子。 基于影响与目标信号相关的频率的加权，进行光谱减法以从单信道信号中去除估计的噪声。 应用频率依赖衰减因子来衰减波束外的频率仓，以产生具有降噪的目标信号。

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