Updating hidden conditional random field model parameters after processing individual training samples
    1.
    发明申请
    Updating hidden conditional random field model parameters after processing individual training samples 有权
    在处理个人培训样本后更新隐藏的条件随机场模型参数

    公开(公告)号:US20070067171A1

    公开(公告)日:2007-03-22

    申请号:US11233148

    申请日:2005-09-22

    IPC分类号: G10L15/00

    CPC分类号: G10L15/063

    摘要: A method and apparatus are provided for training parameters in a hidden conditional random field model for use in speech recognition and phonetic classification. The hidden conditional random field model uses parameterized features that are determined from a segment of speech, and those values are used to identify a phonetic unit for the segment of speech. The parameters are updated after processing of individual training samples.

    摘要翻译: 提供了一种用于训练用于语音识别和语音分类的隐藏条件随机场模型中的参数的方法和装置。 隐藏条件随机场模型使用从语音段确定的参数化特征,并且这些值用于识别语音段的语音单元。 参数在处理单个培训样本后更新。

    Trans-lingual representation of text documents
    2.
    发明授权
    Trans-lingual representation of text documents 有权
    文本文本的跨语言表示

    公开(公告)号:US08738354B2

    公开(公告)日:2014-05-27

    申请号:US12488422

    申请日:2009-06-19

    IPC分类号: G06F17/28 G06F17/20

    CPC分类号: G06F17/28 G06N3/0454

    摘要: A method of creating translingual text representations takes in documents in a first language and in a second language and creates a matrix using the words in the documents to represent which words are present in which language. An algorithm is applied to each matrix such that like documents are placed close to each other and unlike documents are moved far from each other.

    摘要翻译: 创建跨文本表示的方法以第一语言和第二语言获取文档,并且使用文档中的单词创建矩阵来表示以哪种语言存在哪些单词。 一种算法被应用于每个矩阵,使得类似的文档被放置得彼此靠近,并且不同的文档彼此远离地移动。

    System and process for regression-based residual acoustic echo suppression
    3.
    发明授权
    System and process for regression-based residual acoustic echo suppression 有权
    基于回归的残余声学回声抑制的系统和过程

    公开(公告)号:US08416946B2

    公开(公告)日:2013-04-09

    申请号:US12890075

    申请日:2010-09-24

    IPC分类号: H04M9/08

    CPC分类号: H04M9/082

    摘要: A regression-based residual echo suppression (RES) system and process for suppressing the portion of the microphone signal corresponding to a playback of a speaker audio signal that was not suppressed by an acoustic echo canceller (AEC). In general, a prescribed regression technique is used between a prescribed spectral attribute of multiple past and present, fixed-length, periods (e.g., frames) of the speaker signal and the same spectral attribute of a current period (e.g., frame) of the echo residual in the output of the AEC. This automatically takes into consideration the correlation between the time periods of the speaker signal. The parameters of the regression can be easily tracked using adaptive methods. Multiple applications of RES can be used to produce better results and this system and process can be applied to stereo-RES as well.

    摘要翻译: 基于回归的残差回波抑制(RES)系统和用于抑制对应于未被声学回声消除器(AEC)抑制的扬声器音频信号的重放的麦克风信号的部分的处理。 通常,在多个过去和现在,固定长度的扬声器信号的周期(例如,帧)和当前周期(例如,帧)的相同频谱属性之间使用规定的回归技术 AEC输出中的回波残差。 这自动考虑了扬声器信号的时间段之间的相关性。 可以使用自适应方法轻松跟踪回归的参数。 RES的多个应用可以用于产生更好的结果,并且该系统和过程也可以应用于立体声RES。

    Automatic audio gain control for concurrent capture applications
    4.
    发明授权
    Automatic audio gain control for concurrent capture applications 有权
    用于并发捕获应用的自动音频增益控制

    公开(公告)号:US08290181B2

    公开(公告)日:2012-10-16

    申请号:US11084608

    申请日:2005-03-19

    IPC分类号: H03G3/00 H03G9/00

    摘要: A system level automatic gain control (“System AGC”) automatically initializes and controls analog microphone gain in an environment where multiple independent applications simultaneously receive an input from a single analog microphone or microphone array. In one embodiment, the System AGC also prevents those applications from acting to separately control the gain by intercepting external gain control commands and responding to the corresponding application with a corresponding digital gain applied to the input signal from the microphone. Consequently, the System AGC avoids problems relating to oscillations and instability in the microphone gain resulting from multiple applications trying to simultaneously control the gain while preventing each application from adversely affecting the quality of another application's audio capture signal. Further, in one embodiment, the System AGC also acts to maximize the signal to noise (SNR) ratio of the microphone without introducing clipping as a function of a sampled background environment.

    摘要翻译: 在多个独立应用程序同时从单个模拟麦克风或麦克风阵列接收输入的环境中,系统级自动增益控制(系统AGC)自动初始化和控制模拟麦克风增益。 在一个实施例中,系统AGC还防止这些应用通过截取外部增益控制命令来单独地控制增益,并且以对应于来自麦克风的输入信号的相应数字增益作出响应。 因此,系统AGC避免了与多个应用程序尝试同时控制增益相关的麦克风增益的振荡和不稳定性问题,同时防止每个应用程序不利地影响另一应用程序的音频捕获信号的质量。 此外,在一个实施例中,系统AGC还用于使麦克风的信噪比(SNR)最大化,而不会引入作为采样的背景环境的函数的削波。

    TRANS-LINGUAL REPRESENTATION OF TEXT DOCUMENTS
    5.
    发明申请
    TRANS-LINGUAL REPRESENTATION OF TEXT DOCUMENTS 有权
    文本文档的跨文字表示

    公开(公告)号:US20100324883A1

    公开(公告)日:2010-12-23

    申请号:US12488422

    申请日:2009-06-19

    IPC分类号: G06F17/28 G06N3/02 G06F15/18

    CPC分类号: G06F17/28 G06N3/0454

    摘要: A method of creating translingual text representations takes in documents in a first language and in a second language and creates a matrix using the words in the documents to represent which words are present in which language. An algorithm is applied to each matrix such that like documents are placed close to each other and unlike documents are moved far from each other.

    摘要翻译: 创建跨文本表示的方法以第一语言和第二语言获取文档,并且使用文档中的单词创建矩阵来表示以哪种语言存在哪些单词。 一种算法被应用于每个矩阵,使得类似的文档被放置得彼此靠近,并且不同的文档彼此远离地移动。

    Leveraging unlabeled data with a probabilistic graphical model
    6.
    发明申请
    Leveraging unlabeled data with a probabilistic graphical model 有权
    利用概率图形模型利用未标记的数据

    公开(公告)号:US20070005341A1

    公开(公告)日:2007-01-04

    申请号:US11170989

    申请日:2005-06-30

    IPC分类号: G06F17/27

    CPC分类号: G06F17/3071

    摘要: A general probabilistic formulation referred to as ‘Conditional Harmonic Mixing’ is provided, in which links between classification nodes are directed, a conditional probability matrix is associated with each link, and where the numbers of classes can vary from node to node. A posterior class probability at each node is updated by minimizing a divergence between its distribution and that predicted by its neighbors. For arbitrary graphs, as long as each unlabeled point is reachable from at least one training point, a solution generally always exists, is unique, and can be found by solving a sparse linear system iteratively. In one aspect, an automated data classification system is provided. The system includes a data set having at least one labeled category node in the data set. A semi-supervised learning component employs directed arcs to determine the label of at least one other unlabeled category node in the data set.

    摘要翻译: 提供了称为“条件谐波混合”的一般概率公式,其中分类节点之间的链接被引导,条件概率矩阵与每个链路相关联,并且类的数量可以在节点之间变化。 通过最小化其分布与其邻居预测的分布之间的差异来更新每个节点处的后级概率。 对于任意图,只要每个未标记的点从至少一个训练点到达,则通常总是存在的解是唯一的,并且可以通过迭代地求解稀疏线性系统来找到。 一方面,提供了一种自动数据分类系统。 该系统包括在数据集中具有至少一个标记类别节点的数据集。 半监督学习组件使用有向弧来确定数据集中至少一个其他未标记类别节点的标签。

    NOISE-ROBUST FEATURE EXTRACTION USING MULTI-LAYER PRINCIPAL COMPONENT ANALYSIS
    7.
    发明申请
    NOISE-ROBUST FEATURE EXTRACTION USING MULTI-LAYER PRINCIPAL COMPONENT ANALYSIS 有权
    使用多层主成分分析的噪声强度特征提取

    公开(公告)号:US20060217968A1

    公开(公告)日:2006-09-28

    申请号:US11422862

    申请日:2006-06-07

    IPC分类号: G10L19/14

    摘要: Extracting features from signals for use in classification, retrieval, or identification of data represented by those signals uses a “Distortion Discriminant Analysis” (DDA) of a set of training signals to define parameters of a signal feature extractor. The signal feature extractor takes signals having one or more dimensions with a temporal or spatial structure, applies an oriented principal component analysis (OPCA) to limited regions of the signal, aggregates the output of multiple OPCAs that are spatially or temporally adjacent, and applies OPCA to the aggregate. The steps of aggregating adjacent OPCA outputs and applying OPCA to the aggregated values are performed one or more times for extracting low-dimensional noise-robust features from signals, including audio signals, images, video data, or any other time or frequency domain signal. Such extracted features are useful for many tasks, including automatic authentication or identification of particular signals, or particular elements within such signals.

    摘要翻译: 从用于分类,检索或识别由这些信号表示的数据的信号中提取特征使用一组训练信号的“失真判别分析”(DDA)来定义信号特征提取器的参数。 信号特征提取器采用具有时间或空间结构的一个或多个维度的信号,将定向主成分分析(OPCA)应用于信号的有限区域,聚合空间或时间相邻的多个OPCA的输出,并应用OPCA 到总计。 执行聚合相邻OPCA输出并将OPCA应用于聚合值的步骤一次或多次,用于从包括音频信号,图像,视频数据或任何其他时间或频域信号的信号中提取低维噪声鲁棒特征。 这些提取的特征对于许多任务是有用的,包括特定信号的自动认证或识别,或这些信号内的特定元件。

    Automatic audio gain control for concurrent capture applications
    8.
    发明申请
    Automatic audio gain control for concurrent capture applications 有权
    用于并发捕获应用的自动音频增益控制

    公开(公告)号:US20060210096A1

    公开(公告)日:2006-09-21

    申请号:US11084608

    申请日:2005-03-19

    IPC分类号: H03G3/00 H03G9/00

    摘要: A system level automatic gain control (“System AGC”) automatically initializes and controls analog microphone gain in an environment where multiple independent applications simultaneously receive an input from a single analog microphone or microphone array. In one embodiment, the System AGC also prevents those applications from acting to separately control the gain by intercepting external gain control commands and responding to the corresponding application with a corresponding digital gain applied to the input signal from the microphone. Consequently, the System AGC avoids problems relating to oscillations and instability in the microphone gain resulting from multiple applications trying to simultaneously control the gain while preventing each application from adversely affecting the quality of another application's audio capture signal. Further, in one embodiment, the System AGC also acts to maximize the signal to noise (SNR) ratio of the microphone without introducing clipping as a function of a sampled background environment.

    摘要翻译: 系统级自动增益控制(“系统AGC”)在多个独立应用程序同时从单个模拟麦克风或麦克风阵列接收输入的环境中自动初始化和控制模拟麦克风增益。 在一个实施例中,系统AGC还防止这些应用通过截取外部增益控制命令来单独地控制增益,并且以对应于来自麦克风的输入信号的相应数字增益作出响应。 因此,系统AGC避免了与多个应用程序尝试同时控制增益相关的麦克风增益的振荡和不稳定性问题,同时防止每个应用程序不利地影响另一应用程序的音频捕获信号的质量。 此外,在一个实施例中,系统AGC还用于使麦克风的信噪比(SNR)最大化,而不会引入作为采样的背景环境的函数的削波。

    Game-powered search engine
    9.
    发明申请

    公开(公告)号:US20060167874A1

    公开(公告)日:2006-07-27

    申请号:US11041557

    申请日:2005-01-24

    IPC分类号: G06F7/00 G06F17/30

    摘要: The subject invention provides a unique system and method that facilitates an interactive game-powered search engine that serve the purposes of both users who may be looking for information as well as game participants who may desire to earn some reward or level of enjoyment by playing the game. More specifically, the system and method provides feedback to a user based on the user's input string or a string derived therefrom. The feedback can be a response or answer to the user's input in the form of text, an image, audio or sound, video, and/or a URL that is provided by one or more game participants when there is some degree of consistency or agreement between the responses or when individual players have demonstrated good reliability in their responses.

    Auto playlist generation with multiple seed songs

    公开(公告)号:US20060032363A1

    公开(公告)日:2006-02-16

    申请号:US11255365

    申请日:2005-10-21

    申请人: John Platt

    发明人: John Platt

    IPC分类号: G10H1/00 G10H7/00

    摘要: The present invention relates to systems and/or methods that generate playlist(s) for a library or collection of media items via selecting a plurality of seed items, at least one of which is an undesirable seed item. Some of the seed items are desirable indicating that a user prefers additional media items similar to the desirable seed items and others are undesirable indicating that the user prefers additional media items dissimilar to the undesirable seed items. Additionally, the seed items can be weighted to establish a relative importance of the seed items. The invention compares media items in the collection with the seed items and determines which media items are added into the playlist by computation of similarity metrics or values. The playlist can be regenerated by adding desirable seed items to the playlist and removing media items from the playlist (e.g., undesirable seed items).