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    • 2. 发明申请
    • LEARNING SPEECH MODELS FOR MOBILE DEVICE USERS
    • 学习移动设备用户的语音模型
    • WO2013006489A1
    • 2013-01-10
    • PCT/US2012/045101
    • 2012-06-29
    • QUALCOMM INCORPORATEDGROKOP, Leonard, HenryNARAYANAN, Vidya
    • GROKOP, Leonard, HenryNARAYANAN, Vidya
    • G10L15/06
    • G10L15/063G06N7/005G10L2015/0631
    • Techniques are provided to recognize a speaker's voice. In one embodiment, received audio data may be separated into a plurality of signals. For each signal, the signal may be associated with value/s for one or more features (e.g., Mel-Frequency Cepstral coefficients). The received data may be clustered (e.g., by clustering features associated with the signals). A predominate voice cluster may be identified and associated with a user. A speech model (e.g., a Gaussian Mixture Model or Hidden Markov Model) may be trained based on data associated with the predominate cluster. A received audio signal may then be processed using the speech model to, e.g.,: determine who was speaking; determine whether the user was speaking; determining whether anyone was speaking; and/or determine what words were said. A context of the device or the user may then be inferred based at least partly on the processed signal.
    • 提供技术来识别扬声器的声音。 在一个实施例中,所接收的音频数据可以被分成多个信号。 对于每个信号,信号可以与一个或多个特征(例如,梅尔频率倒频谱系数)的值/ s相关联。 接收到的数据可以被聚类(例如,通过聚集与信号相关联的特征)。 可以识别主要的语音群集并且与用户相关联。 可以基于与主要簇相关联的数据来训练语音模型(例如,高斯混合模型或隐马尔可夫模型)。 然后可以使用语音模型来处理接收到的音频信号,例如:确定谁在说话; 确定用户是否在说话; 确定是否有人在说话; 和/或确定说什么话。 可以至少部分地基于经处理的信号来推断设备或用户的上下文。
    • 4. 发明申请
    • DEVICE POSITION ESTIMATES FROM MOTION AND AMBIENT LIGHT CLASSIFIERS
    • 设备位置从运动和环境光分类器估计
    • WO2012141811A1
    • 2012-10-18
    • PCT/US2012/027105
    • 2012-02-29
    • QUALCOMM IncorporatedGROKOP, Leonard HenryNARAYANAN, Vidya
    • GROKOP, Leonard HenryNARAYANAN, Vidya
    • G01S5/16
    • G01S5/16G01C19/34G01C19/44G01C21/165G06F1/1686G06F1/1694H04M1/72522
    • A position estimate for a mobile device is generated using data from motion sensors, such as accelerometers, magnetometers, and/or gyroscopes, and data from light sensors, such as an ambient light sensor, proximity sensor and/or camera intensity sensor. A plurality of proposed positions with associated likelihoods is generated by analyzing information from the motion sensors and a list of candidate positions is produced based on information from the light sensors. At least one of the plurality of proposed positions is eliminated using the list of candidate positions and a position estimate for the mobile device is determined based on the remaining proposed positions and associated likelihoods. The proposed positions may be generated by extracting features from the information from the motion sensors and using models to generate likelihoods for the proposed positions. The likelihoods may be filtered over time. Additionally, a confidence metric may be generated for the estimated position.
    • 使用来自诸如加速度计,磁力计和/或陀螺仪的运动传感器的数据以及来自诸如环境光传感器,接近传感器和/或照相机强度传感器的光传感器的数据来生成移动设备的位置估计。 通过分析来自运动传感器的信息来产生具有相关似然性的多个提出的位置,并且基于来自光传感器的信息产生候选位置的列表。 使用候选位置的列表来消除多个提出的位置中的至少一个,并且基于剩余的建议位置和相关联的可能性来确定移动设备的位置估计。 可以通过从运动传感器的信息中提取特征并使用模型来产生所提出的位置的可能性来产生所提出的位置。 可能性可能会随时间过滤。 另外,可以为估计位置生成置信度量度。
    • 7. 发明申请
    • FLEXIBLE DATA DOWNLOAD MODELS FOR AUGMENTED REALITY
    • 适用于现实的灵活数据下载模型
    • WO2012012781A1
    • 2012-01-26
    • PCT/US2011/045111
    • 2011-07-22
    • QUALCOMM INCORPORATEDNARAYANAN, Vidya
    • NARAYANAN, Vidya
    • G06F17/30
    • G06F17/30244G06F17/30241
    • In an AR system, method for operating same, a mobile device, and method for operating same, flexible loxels are used that may be different for different image data providers. This enables AR applications to download smaller loxels which have more information, such as dense areas, like in cities, or larger loxels which have less information, like, for example, desert areas. Data downloads may take into account client orientation and direction of motion to determine incremental data that need to be downloaded as the client moves. The loxels are coded with loxel identifiers mapped to location information, so only the necessary loxels for a particular application need be downloaded, allowing the client to autonomously decide when to acquire new image data and how much data to acquire.
    • 在AR系统中,使用对于不同的图像数据提供者可能不同的用于操作其的方法,移动设备和用于操作相同的柔性loxels的方法。 这使得AR应用程序可以下载更多的信息,比如像城市这样的密集区域,或者具有较少信息的较大的loux,比如沙漠地区的信息更小的loxels。 数据下载可能会考虑到客户端的方向和运动方向,以确定客户端移动时需要下载的增量数据。 利用映射到位置信息的loxel标识符对loxel进行编码,因此只需要下载特定应用程序所需的loxels,从而允许客户自主决定何时获取新的图像数据以及要获取多少数据。