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61. 发明申请

US20180061422A1 ORIENTING A MICROPHONE ARRAY TO A USER LOCATION 有权
公开(公告)号：US20180061422A1
公开(公告)日：2018-03-01
申请号：US15250676
申请日：2016-08-29
申请人： LENOVO (Singapore) PTE. LTD.
发明人： Song Wang , John Weldon Nicholson , Ming Qian
IPC分类号： G10L17/22 , G10L17/04 , G10L17/18
CPC分类号： G10L17/22 , G10L15/22 , G10L17/04 , G10L17/18 , G10L2015/223 , H04R1/326 , H04R3/005 , H04R2430/20 , H04R2499/11
摘要： For orienting a microphone array to a user location, a processor detects a user location with a presence sensor that detects a user using electromagnetic signals. In addition, the processor orients a microphone array to the user location.

62. 发明授权

US09824692B1 End-to-end speaker recognition using deep neural network 有权
公开(公告)号：US09824692B1
公开(公告)日：2017-11-21
申请号：US15262748
申请日：2016-09-12
申请人： PINDROP SECURITY, INC.
发明人： Elie Khoury , Matthew Garland
IPC分类号： G10L17/18 , G10L15/16 , G10L17/04 , G10L17/08 , G10L17/02 , G10L17/22 , G06N3/04 , G06N3/08
CPC分类号： G10L17/08 , G06N3/04 , G06N3/08 , G10L15/16 , G10L17/02 , G10L17/04 , G10L17/18 , G10L17/22
摘要： The present invention is directed to a deep neural network (DNN) having a triplet network architecture, which is suitable to perform speaker recognition. In particular, the DNN includes three feed-forward neural networks, which are trained according to a batch process utilizing a cohort set of negative training samples. After each batch of training samples is processed, the DNN may be trained according to a loss function, e.g., utilizing a cosine measure of similarity between respective samples, along with positive and negative margins, to provide a robust representation of voiceprints.

63. 发明申请

US20170287487A1 SPEAKER IDENTIFICATION 审中-公开
公开(公告)号：US20170287487A1
公开(公告)日：2017-10-05
申请号：US15624760
申请日：2017-06-16
申请人： Google Inc.
发明人： Matthew Sharifi , Ignacio Lopez Moreno , Ludwig Schmidt
IPC分类号： G10L17/02 , G10L17/08 , G10L25/51 , G10L17/18
CPC分类号： G10L17/02 , G10L17/005 , G10L17/08 , G10L17/18 , G10L25/51
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing speaker identification. In some implementations, data identifying a media item including speech of a speaker is received. Based on the received data, one or more other media items that include speech of the speaker are identified. One or more search results are generated that each reference a respective media item of the one or more other media items that include speech of the speaker. The one or more search results are provided for display.

64. 发明申请

US20170069327A1 Neural Networks For Speaker Verification 有权
标题翻译：用于演讲者验证的神经网络
公开(公告)号：US20170069327A1
公开(公告)日：2017-03-09
申请号：US14846187
申请日：2015-09-04
申请人： Google Inc.
发明人： Georg Heigold , Samy Bengio , Ignacio Lopez Moreno
IPC分类号： G10L17/18 , G10L17/04
CPC分类号： G10L17/18 , G10L17/02 , G10L17/04
摘要： This document generally describes systems, methods, devices, and other techniques related to speaker verification, including (i) training a neural network for a speaker verification model, (ii) enrolling users at a client device, and (iii) verifying identities of users based on characteristics of the users' voices. Some implementations include a computer-implemented method. The method can include receiving, at a computing device, data that characterizes an utterance of a user of the computing device. A speaker representation can be generated, at the computing device, for the utterance using a neural network on the computing device. The neural network can be trained based on a plurality of training samples that each: (i) include data that characterizes a first utterance and data that characterizes one or more second utterances, and (ii) are labeled as a matching speakers sample or a non-matching speakers sample.
摘要翻译：本文件通常描述与扬声器验证相关的系统，方法，设备和其他技术，包括（i）训练用于说话者验证模型的神经网络，（ii）在客户端设备上注册用户，以及（iii）验证用户的身份基于用户声音的特点。一些实现包括计算机实现的方法。该方法可以包括在计算设备处接收表征计算设备的用户的话语的数据。可以在计算设备处产生使用计算设备上的神经网络的话语的扬声器表示。可以基于多个训练样本来训练神经网络，每个训练样本：（i）包括表征第一话语的数据和表征一个或多个第二话语的数据，以及（ii）被标记为匹配的说话者样本或非匹配音箱样品。

65. 发明申请

US20160358610A1 METHOD AND DEVICE FOR VOICEPRINT RECOGNITION 审中-公开
标题翻译：用于VOICEPRINT识别的方法和装置
公开(公告)号：US20160358610A1
公开(公告)日：2016-12-08
申请号：US15240696
申请日：2016-08-18
申请人： Tencent Technology (Shenzhen) Company Limited
发明人： Eryu WANG , Li LU , Xiang ZHANG , Haibo LIU , Lou LI , Feng RAO , Duling LU , Shuai YUE , Bo CHEN
IPC分类号： G10L17/18 , G10L17/04 , G10L17/02 , G10L17/08
CPC分类号： G10L17/18 , G10L17/02 , G10L17/04 , G10L17/08
摘要： A method is performed at a device having one or more processors and memory. The device establishes a first-level Deep Neural Network (DNN) model based on unlabeled speech data, the unlabeled speech data containing no speaker labels and the first-level DNN model specifying a plurality of basic voiceprint features for the unlabeled speech data. The device establishes a second-level DNN model by tuning the first-level DNN model based on labeled speech data, the labeled speech data containing speech samples with respective speaker labels, wherein the second-level DNN model specifies a plurality of high-level voiceprint features. Using the second-level DNN model, registers a first high-level voiceprint feature sequence for a user based on a registration speech sample received from the user. The device performs speaker verification for the user based on the first high-level voiceprint feature sequence registered for the user.
摘要翻译：在具有一个或多个处理器和存储器的设备上执行一种方法。该设备基于未标记的语音数据建立第一级深神经网络（DNN）模型，不包含扬声器标签的未标记语音数据和指定用于未标记语音数据的多个基本声纹特征的第一级DNN模型。该设备通过基于标记的语音数据调整第一级DNN模型来建立第二级DNN模型，该标记语音数据包含具有相应扬声器标签的语音样本，其中第二级DNN模型指定多个高级声纹特征。使用第二级DNN模型，基于从用户接收的注册语音样本，为用户注册第一高级声纹特征序列。该设备基于为用户注册的第一个高级声纹特征序列，为用户执行扬声器验证。

66. 发明申请

US20160293167A1 SPEAKER RECOGNITION USING NEURAL NETWORKS 审中-公开
标题翻译：使用神经网络的扬声器识别
公开(公告)号：US20160293167A1
公开(公告)日：2016-10-06
申请号：US15179717
申请日：2016-06-10
申请人： Google Inc.
发明人： Yu-hsin Joyce Chen , Ignacio Lopez Moreno , Tara N. Sainath , Maria Carolina Parada San Martin
IPC分类号： G10L17/18 , G10L17/22 , G10L17/08
CPC分类号： G10L17/18 , G06N3/0454 , G10L17/08 , G10L17/22 , H04N21/23406 , H04N21/23476 , Y10S707/99953
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing speaker verification. In one aspect, a method includes accessing a neural network having an input layer that provides inputs to a first hidden layer whose nodes are respectively connected to only a proper subset of the inputs from the input layer. Speech data that corresponds to a particular utterance may be provided as input to the input layer of the neural network. A representation of activations that occur in response to the speech data at a particular layer of the neural network that was configured as a hidden layer during training of the neural network may be generated. A determination of whether the particular utterance was likely spoken by a particular speaker may be made based at least on the generated representation. An indication of whether the particular utterance was likely spoken by the particular speaker may be provided.
摘要翻译：方法，系统和装置，包括在计算机存储介质上编码的用于执行说话者验证的计算机程序。一方面，一种方法包括访问具有输入层的神经网络，所述输入层向第一隐藏层提供输入，所述第一隐藏层的节点仅分别连接到来自输入层的输入的适当子集。可以将对应于特定话语的语音数据提供给神经网络的输入层的输入。可以生成在神经网络的训练期间被配置为隐藏层的神经网络的特定层响应于语音数据而发生的激活的表示。可以至少基于所生成的表示来确定特定说话者是否可能说出特定话语的确定。可以提供特定说话者是否可能说出特定话语的指示。

67. 发明申请

US20160275953A1 SPEAKER IDENTIFICATION 审中-公开
标题翻译：扬声器识别
公开(公告)号：US20160275953A1
公开(公告)日：2016-09-22
申请号：US15170264
申请日：2016-06-01
申请人： Google Inc.
发明人： Matthew Sharifi , Ignacio Lopez Moreno , Ludwig Schmidt
IPC分类号： G10L17/08 , G10L17/02 , G10L17/18 , G10L25/51
CPC分类号： G10L17/02 , G10L17/005 , G10L17/08 , G10L17/18 , G10L25/51
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing speaker identification. In some implementations, data identifying a media item including speech of a speaker is received. Based on the received data, one or more other media items that include speech of the speaker are identified. One or more search results are generated that each reference a respective media item of the one or more other media items that include speech of the speaker. The one or more search results are provided for display.
摘要翻译：方法，系统和装置，包括在计算机存储介质上编码的用于执行说话人识别的计算机程序。在一些实现中，接收识别包括说话者的语音的媒体项目的数据。基于接收的数据，识别包括说话者的语音的一个或多个其他媒体项目。生成一个或多个搜索结果，每个引用包括说话者的语音的一个或多个其他媒体项的相应媒体项。一个或多个搜索结果被提供用于显示。

68. 发明申请

US20230112265A1 SEPARATING SPEECH BY SOURCE IN AUDIO RECORDINGS BY PREDICTING ISOLATED AUDIO SIGNALS CONDITIONED ON SPEAKER REPRESENTATIONS 有权
公开(公告)号：US20230112265A1
公开(公告)日：2023-04-13
申请号：US17967726
申请日：2022-10-17
申请人： Google LLC
发明人： Neil Zeghidour , David Grangier
IPC分类号： G10L21/028 , G06N3/08 , G10L17/04 , G10L17/18 , G10L21/0316 , G06N3/045
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing speech separation. One of the methods includes obtaining a recording comprising speech from a plurality of speakers; processing the recording using a speaker neural network having speaker parameter values and configured to process the recording in accordance with the speaker parameter values to generate a plurality of per-recording speaker representations, each speaker representation representing features of a respective identified speaker in the recording; and processing the per-recording speaker representations and the recording using a separation neural network having separation parameter values and configured to process the recording and the speaker representations in accordance with the separation parameter values to generate, for each speaker representation, a respective predicted isolated audio signal that corresponds to speech of one of the speakers in the recording.

69. 发明申请

US20230095988A1 SYSTEMS AND METHODS FOR PERFORMING COMMANDS IN A VEHICLE USING SPEECH AND IMAGE RECOGNITION 有权
公开(公告)号：US20230095988A1
公开(公告)日：2023-03-30
申请号：US18062163
申请日：2022-12-06
申请人： NVIDIA Corporation
发明人： Sumit Bhattacharya , Jason Conrad Roche , Niranjan Avadhanam
IPC分类号： B60R25/01 , B60R25/25 , B60R25/30 , G05B13/02 , G06F21/32 , G06N3/08 , G10L17/00 , G10L17/06 , G10L17/18 , G06V10/25 , G06V20/59
摘要： Systems and methods are disclosed herein for implementation of a vehicle command operation system that may use multi-modal technology to authenticate an occupant of the vehicle to authorize a command and receive natural language commands for vehicular operations. The system may utilize sensors to receive data indicative of a voice command from an occupant of the vehicle. The system may receive second sensor data to aid in the determination of the corresponding vehicular operation in response to the received command. The system may retrieve authentication data for the occupants of the vehicle. The system authenticates the occupant to authorize a vehicular operation command using a neural network based on at least one of the first sensor data, the second sensor data, and the authentication data. Responsive to the authentication, the system may authorize the operation to be performed in the vehicle based on the vehicular operation command.

70. 发明授权

US11615760B2 Controlling of device based on user recognition utilizing vision and speech features 有权
公开(公告)号：US11615760B2
公开(公告)日：2023-03-28
申请号：US17101770
申请日：2020-11-23
申请人： LG ELECTRONICS INC.
发明人： Changseok Cho , Woonghee Park , Hyunok Lee , Mansoo Sin , Sanghoon Song , Sangkuk Jeon , Cheol Kang
IPC分类号： G09G5/00 , G06N3/08 , G06N3/04 , G06F3/01 , G06F3/16 , G10L17/18 , G10L25/51 , G06F1/3231 , G06V40/10
摘要： An artificial intelligence-based control method is disclosed. In an artificial intelligence-based control method according to an exemplary embodiment of the present disclosure, when a user approaches within a set sensing range of a device, the device may capture a user image and predict whether the user has an intent to use the device by using motion features included in the captured image. An AI control method of the present disclosure may be associated with an artificial intelligent module, an unmanned aerial vehicle (UAV), a robot, an augmented reality (AR) device, a virtual reality (VR) device, a 5G service-related device, etc.

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