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    • 4. 发明申请
    • TRANSLATING LANGUAGE CHARACTERS IN MEDIA CONTENT
    • 翻译媒体内容中的语言特征
    • US20130103383A1
    • 2013-04-25
    • US13277109
    • 2011-10-19
    • Jun DuLei SunJian SunQiang Huo
    • Jun DuLei SunJian SunQiang Huo
    • G06F17/28
    • G06F17/289G06F3/04842G06F3/0488G06F17/30253
    • Some implementations disclosed herein provide techniques and arrangements to enable translating language characters in media content. For example, some implementations receive a user selection of a first portion of media content. Some implementations disclosed herein may, based on the first portion, identify a second portion of the media content. The second portion of the media content may include one or more first characters of a first language. Some implementations disclosed herein may create an image that includes the second portion of the media content and may send the image to a server. Some implementations disclosed herein may receive one or more second characters of a second language corresponding to a translation of the one or more first characters of the first language from the server.
    • 本文公开的一些实施例提供了能够在媒体内容中翻译语言字符的技术和布置。 例如,一些实现接收用户对媒体内容的第一部分的选择。 本文公开的一些实施例可以基于第一部分标识媒体内容的第二部分。 媒体内容的第二部分可以包括第一语言的一个或多个第一字符。 本文公开的一些实现方式可以创建包括媒体内容的第二部分并且可以将图像发送到服务器的图像。 本文公开的一些实现方式可以从服务器接收对应于第一语言的一个或多个第一字符的翻译的第二语言的一个或多个第二字符。
    • 5. 发明授权
    • Rotation-free recognition of handwritten characters
    • 无旋转识别手写字符
    • US08977042B2
    • 2015-03-10
    • US13575021
    • 2012-03-23
    • Qiang HuoJun Du
    • Qiang HuoJun Du
    • G06K9/62G06K9/00G06K9/32G06K9/42
    • G06K9/6256G06K9/00409G06K9/3283G06K9/42G06K9/6271G06K9/6821G06K2209/01G06K2209/011
    • A character recognition system receives an unknown character and recognizes the character based on a pre-trained recognition model. Prior to recognizing the character, the character recognition system may pre-process the character to rotate the character to a normalized orientation. By rotating the character to a normalized orientation in both training and recognition stages, the character recognition system releases the pre-trained recognition model from considering character prototypes in different orientations and thereby speeds up recognition of the unknown character. In one example, the character recognition system rotates the character to the normalized orientation by aligning a line between a sum of coordinates of starting points and a sum of coordinates of ending points of each stroke of the character with a normalized direction.
    • 字符识别系统接收未知字符并且基于预先训练的识别模型识别角色。 在识别字符之前,字符识别系统可以预处理字符以将字符旋转到归一化方向。 通过在训练和识别阶段将角色旋转到归一化方向,角色识别系统通过以不同方向考虑角色原型来释放预训练的识别模型,从而加快对未知角色的识别。 在一个示例中,字符识别系统通过将起始点的坐标之和与字符的每个笔画的终点的坐标之和与归一化方向对齐来将字符旋转到归一化方向。
    • 7. 发明申请
    • Petroleum Hydrocarbon cracking catalyst that contains rare earth zeolitey and its preparation
    • 含有稀土沸石的石油烃裂解催化剂及其制备方法
    • US20060199725A1
    • 2006-09-07
    • US10533488
    • 2003-10-28
    • Jun DuZheng LiZhijian DaMingyuan He
    • Jun DuZheng LiZhijian DaMingyuan He
    • B01J29/08B01J21/00
    • C10G47/02B01J29/088B01J2229/16B01J2229/32B01J2229/36B01J2229/40B01J2229/42C10G11/05C10G47/16C10G2300/107C10G2300/1074C10G2300/1077C10G2400/02C10L1/06
    • The invention discloses a rare-earth Y-zeolite-containing catalyst for cracking hydrocarbons and a method for preparing the same. The catalyst is characterized in that the rare-earth content in crystal lattice of the rare-earth Y-zeolite, calculated in RE2O3, is from 4 to 15% by weight, the original unit cell size is from 2.440 nm to 2.465 nm and the equilibrium unit cell size after 100% steam-aging treatment at 800° C. for 17 hours is larger than 2.435 nm. The catalyst is obtained in the following steps: the rare-earth Y-zeolite is dried first till its water content less than 10% by weight, then in a weight ratio of SiCl4:Y-zeolite=0.1˜0.9:1, reacts with SiCl4 gas carried by dry air, further is purged by dry air and washed by decationized water to remove the soluble by-products; the resulted rare-earth Y-zeolite is mixed with a binder and a clay, pulped and formed by spary drying. The zeolite content of the catalyst disclosed in present invention decreases 5˜25% by weight compared to the catalyst prepared in prior art for cracking heavy oil and decreasing olefin content. The catalyst is characterized with good cracking activity, high hydrothermal stability, and high conversion of heavy oil as well as excellent selectivity of gasoline, dry gas and coke; moreover, the olefin content in the produced gasoline decreases effectively.
    • 本发明公开了一种用于裂化烃的稀土Y-沸石催化剂及其制备方法。 催化剂的特征在于,在RE 2 O 3 3中计算的稀土Y-沸石的晶格中的稀土含量为4〜15% ,原始晶胞尺寸为2.440nm至2.465nm,并且在800℃下经100%蒸汽老化处理17小时后的平衡晶胞尺寸大于2.435nm。 催化剂按以下步骤得到:首先将稀土Y-沸石干燥至其含水量低于10重量%,然后以SiCl 4重量比:Y-沸石= 0.1〜0.9:1,与干燥空气携带的SiCl 4气体反应,进一步用干燥空气清洗,用去离子水洗涤除去可溶性副产物; 将所得到的稀土Y沸石与粘合剂和粘土混合,通过喷雾干燥制浆并形成。 与现有技术中制备的催化剂相比,本发明公开的催化剂的沸石含量降低了5〜25重量%,用于裂化重油和降低烯烃含量。 催化剂的特点是具有良好的开裂活性,高水稳定性,重油转化率高,以及汽油,干气和焦炭的优异选择性; 此外,生产汽油中的烯烃含量有效降低。
    • 8. 发明授权
    • Translating language characters in media content
    • 翻译媒体内容中的语言字符
    • US09251144B2
    • 2016-02-02
    • US13277109
    • 2011-10-19
    • Jun DuLei SunJian SunQiang Huo
    • Jun DuLei SunJian SunQiang Huo
    • G06F17/28G06F3/0488G06F17/30G06F3/0484
    • G06F17/289G06F3/04842G06F3/0488G06F17/30253
    • Some implementations disclosed herein provide techniques and arrangements to enable translating language characters in media content. For example, some implementations receive a user selection of a first portion of media content. Some implementations disclosed herein may, based on the first portion, identify a second portion of the media content. The second portion of the media content may include one or more first characters of a first language. Some implementations disclosed herein may create an image that includes the second portion of the media content and may send the image to a server. Some implementations disclosed herein may receive one or more second characters of a second language corresponding to a translation of the one or more first characters of the first language from the server.
    • 本文公开的一些实施例提供了能够在媒体内容中翻译语言字符的技术和布置。 例如,一些实现接收用户对媒体内容的第一部分的选择。 本文公开的一些实施例可以基于第一部分标识媒体内容的第二部分。 媒体内容的第二部分可以包括第一语言的一个或多个第一字符。 本文公开的一些实现方式可以创建包括媒体内容的第二部分并且可以将图像发送到服务器的图像。 本文公开的一些实现方式可以从服务器接收对应于第一语言的一个或多个第一字符的翻译的第二语言的一个或多个第二字符。
    • 9. 发明申请
    • FEATURE COMPENSATION APPROACH TO ROBUST SPEECH RECOGNITION
    • 强调语音识别的特征补偿方法
    • US20100262423A1
    • 2010-10-14
    • US12422314
    • 2009-04-13
    • Qiang HuoJun Du
    • Qiang HuoJun Du
    • G10L15/20
    • G10L15/20G10L21/0208
    • Described is a technology by which a feature compensation approach to speech recognition uses a high-order vector Taylor series (HOVTS) approximation of a model of distortions to improve recognition accuracy. Speech recognizer models trained with clean speech degrade when later dealing with speech that is corrupted by additive noises and convolutional distortions. The approach attempts to remove any such noise/distortions from the input speech. To use the HOVTS approximation, a Gaussian mixture model is trained and used to convert cepstral domain feature vectors to log spectrum components. HOVTS computes statistics for the components, which are transformed back to the cepstral domain. A noise/distortion estimate is obtained, and used to provide a clean speech estimate to the recognizer.
    • 描述了一种用于语音识别的特征补偿方法使用失真模型的高阶向量泰勒级数(HOVTS)近似来提高识别精度的技术。 用后来处理由附加噪声和卷积失真破坏的语音的语音识别器模型训练有素质。 该方法尝试从输入语音中去除任何这样的噪声/失真。 为了使用HOVTS近似,训练高斯混合模型并将其用于将倒谱域特征向量转换为对数谱分量。 HOVTS计算组件的统计数据,这些组件被转换回到倒谱域。 获得噪声/失真估计,并用于向识别器提供清晰的语音估计。
    • 10. 发明申请
    • REMOVING NOISE FROM SPEECH
    • 从语音中消除噪音
    • US20100145687A1
    • 2010-06-10
    • US12327824
    • 2008-12-04
    • Qiang HuoJun Du
    • Qiang HuoJun Du
    • G10L21/02G10L11/04G10L11/02
    • G10L21/0208G10L2021/02168
    • Method for removing noise from a digital speech waveform, including receiving the digital speech waveform having the noise contained therein, segmenting the digital speech waveform into one or more frames, each frame having a clean portion and a noisy portion, extracting a feature component from each frame, creating an nonlinear speech distortion model from the feature components, creating a statistical noise model by making a Piecewise Linear Approximation (PLA) of the nonlinear speech distortion model, determining the clean portion of each frame using the statistical noise model, a log power spectra of each frame, and a model of a digital speech waveform recorded in a noise controlled environment, and constructing a clean digital speech waveform from each clean portion of each frame.
    • 用于从数字语音波形中去除噪声的方法,包括接收包含在其中的噪声的数字语音波形,将数字语音波形分割成一个或多个帧,每帧具有干净部分和噪声部分,从每个帧中提取特征成分 从特征部分创建非线性语音失真模型,通过使用非线性语音失真模型的分段线性逼近(PLA)创建统计噪声模型,使用统计噪声模型确定每个帧的干净部分,对数功率 每个帧的频谱,以及记录在噪声控制环境中的数字语音波形的模型,以及从每个帧的每个清洁部分构建干净的数字语音波形。