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1. 发明授权

US09405893B2 Biometric authentication 有权
标题翻译：生物识别认证
公开(公告)号：US09405893B2
公开(公告)日：2016-08-02
申请号：US14172928
申请日：2014-02-05
申请人： International Business Machines Corporation
发明人： Hagai Aronowitz , Amir Geva , Ron Hoory , David Nahamoo , Jason William Pelecanos , Orith Toledo-Ronen
IPC分类号： G06F21/32 , G06K9/00 , G06N99/00 , G06K9/62
CPC分类号： G06F21/32 , G06K9/00892 , G06K9/629 , G06N99/005
摘要： A method comprising using at least one hardware processor for: providing a set of development supervectors representing features of biometric samples of multiple subjects, the biometric samples being of at least a first and a second different biometric modalities; providing at least a first and a second enrollment supervectors representing features of at least a first and a second enrollment biometric samples of a target subject correspondingly, wherein the at least first and second enrollment samples are of the at least first and the second different biometric modalities correspondingly; providing at least a first and a second verification supervectors representing features of at least a first and a second verification biometric samples of the target subject correspondingly, wherein the at least first and second verification samples are of the at least first and second different biometric modalities correspondingly; concatenating the development supervectors to a set of development generic supervector, the at least first and second enrollment supervectors to a single enrollment generic supervector and the at least first and second verification supervectors to a single verification generic supervector; and verifying an identity of the target subject based on a fused score calculated for the verification generic supervector, wherein the fused score is calculated based on the enrollment generic supervector and the set of development generic supervectors.
摘要翻译：一种方法，包括使用至少一个硬件处理器：提供表示多个对象的生物特征样本的特征的一组开发超级生物，所述生物特征样本是至少第一和第二不同的生物特征模态; 提供至少第一和第二注册超级代理，其对应地代表目标对象的至少第一和第二注册生物特征样本的特征，其中所述至少第一和第二注册样本是至少第一和第二不同生物特征模态相应地提供至少第一和第二验证超级向量，其相应地代表目标对象的至少第一和第二验证生物测定样本的特征，其中所述至少第一和第二验证样本相应地具有至少第一和第二不同生物特征模态 ; 将开发超级用户连接到一组开发通用超向量，至少第一和第二注册超级用户单个注册通用超向量，以及至少第一和第二验证超级用户到单个验证通用超向量; 以及基于针对所述验证通用超向量计算的融合分数来验证所述目标对象的身份，其中，基于所述注册通用超向量和所述开发通用超级向量集合来计算所述融合分数。

2. 发明申请

US20200065716A1 LEARNING SENTIMENT COMPOSITION FROM SENTIMENT LEXICONS 审中-公开
公开(公告)号：US20200065716A1
公开(公告)日：2020-02-27
申请号：US16191478
申请日：2018-11-15
申请人： International Business Machines Corporation
发明人： Ranit Aharonov , Roy Bar-Haim , Alon Halfon , Charles Arthur Jochim , Amir Menczel , Noam Slonim , Orith Toledo-Ronen
IPC分类号： G06N99/00 , G06F17/18
摘要： A method including: generating, from a text corpus, a lexicon of unigrams and bigrams comprising an embedding for each of said unigrams and bigrams; training a machine learning classifier on a training set comprising a subset of said lexicon, wherein each of said unigrams and bigrams in said subset has a sentiment label; applying said machine learning classifier to said lexicon, to (i) predict a sentiment of each of said unigrams and bigrams, and (ii) update said lexicon with the predicted sentiments; and performing statistical analysis on said updated lexicon, to extract one or more sentiment composition lexicons, wherein each of said one or more sentiment composition lexicons is associated with a sentiment composition class.

3. 发明申请

US20160055844A1 SYSTEMS AND METHODS FOR DETECTION OF TARGET AND NON-TARGET USERS USING MULTI-SESSION INFORMATION 有权
标题翻译：使用多个会话信息检测目标和非目标用户的系统和方法
公开(公告)号：US20160055844A1
公开(公告)日：2016-02-25
申请号：US14465415
申请日：2014-08-21
申请人： International Business Machines Corporation
发明人： Hagai Aronowitz , Shay Ben-David , David Nahamoo , Jason W. Pelecanos , Orith Toledo-Ronen
IPC分类号： G10L15/02 , G10L15/22
CPC分类号： G10L17/06
摘要： Systems and methods for maintaining speaker recognition performance are provided. A method for maintaining speaker recognition performance, comprises training a plurality of models respectively corresponding to speaker recognition scores from a plurality of speakers over a plurality of sessions, and using the plurality of models to conclude whether a speaker seeking access to an environment is a non-ideal target speaker or a non-ideal non-target speaker. Using the plurality of models to conclude comprises calculating a first probability that the speaker seeking access is the non-ideal target speaker, calculating a second probability that the speaker seeking access is the non-ideal non-target speaker, and determining whether the first probability, the second probability or a sum of the first probability and the second probability is above a probability threshold.
摘要翻译：提供了保持扬声器识别性能的系统和方法。一种用于维护说话者识别性能的方法，包括：通过多个会话从多个扬声器分别对应于说话者识别分数来训练多个模型，并且使用多个模型来确定寻求对环境的访问是否是非主要目标扬声器或非理想非目标扬声器。使用多个模型来得出结论包括：计算说话人寻求访问的是第一概率是非理想目标说话者，计算说话者寻求访问的第二概率是非理想非目标说话者，并且确定第一概率，第二概率或第一概率和第二概率的和高于概率阈值。

4. 发明申请

US20220147574A9 EXPERT STANCE CLASSIFICATION USING COMPUTERIZED TEXT ANALYTICS 有权
公开(公告)号：US20220147574A9
公开(公告)日：2022-05-12
申请号：US16454083
申请日：2019-06-27
申请人： International Business Machines Corporation
发明人： ROY BAR-HAIM , Noam Slonim , Orith Toledo-Ronen
IPC分类号： G06F16/9032 , G06F17/27 , G06K9/00 , G06F16/955
摘要： A computerized text analysis method that comprises: searching a resource of information with a search query comprising at least one of: (a) the specific debatable topic, and (b) a personal derivation of the specific debatable topic, to obtain a list of indices whose index subject contains the personal derivation and/or the specific debatable topic; determining, by applying a rule-based classifier, whether the index subject of each of the indices is (i) in favor of the debatable topic or (ii) against the debatable topic; detecting, in each of the indices, hyperlinks to encyclopedic entries whose entry subjects are person names; and determining that: if the index subject of each of the one or more indices is in favor of the specific debatable topic, then the persons are in favor of the specific debatable topic, and vice versa.

5. 发明申请

US20180260476A1 EXPERT STANCE CLASSIFICATION USING COMPUTERIZED TEXT ANALYTICS 审中-公开
公开(公告)号：US20180260476A1
公开(公告)日：2018-09-13
申请号：US15453918
申请日：2017-03-09
申请人： International Business Machines Corporation
发明人： Roy Bar-Haim , Noam Slonim , Orith Toledo-Ronen
IPC分类号： G06F17/30
CPC分类号： G06F16/353 , G06F16/31 , G06F16/3334 , G06F16/334 , G06F16/93 , G06F16/9566 , G06F17/27
摘要： A computerized text analysis method that comprises: searching a resource of information with a search query comprising at least one of: (a) the specific debatable topic, and (b) a personal derivation of the specific debatable topic, to obtain a list of indices whose index subject contains the personal derivation and/or the specific debatable topic; determining, by applying a rule-based classifier, whether the index subject of each of the indices is (i) in favor of the debatable topic or (ii) against the debatable topic; detecting, in each of the indices, hyperlinks to encyclopedic entries whose entry subjects are person names; and determining that: if the index subject of each of the one or more indices is in favor of the specific debatable topic, then the persons are in favor of the specific debatable topic, and vice versa.

6. 发明授权

US09837080B2 Detection of target and non-target users using multi-session information 有权
公开(公告)号：US09837080B2
公开(公告)日：2017-12-05
申请号：US14465415
申请日：2014-08-21
申请人： International Business Machines Corporation
发明人： Hagai Aronowitz , Shay Ben-David , David Nahamoo , Jason W. Pelecanos , Orith Toledo-Ronen
IPC分类号： G10L17/06
CPC分类号： G10L17/06
摘要： Systems and methods for maintaining speaker recognition performance are provided. A method for maintaining speaker recognition performance, comprises training a plurality of models respectively corresponding to speaker recognition scores from a plurality of speakers over a plurality of sessions, and using the plurality of models to conclude whether a speaker seeking access to an environment is a non-ideal target speaker or a non-ideal non-target speaker. Using the plurality of models to conclude comprises calculating a first probability that the speaker seeking access is the non-ideal target speaker, calculating a second probability that the speaker seeking access is the non-ideal non-target speaker, and determining whether the first probability, the second probability or a sum of the first probability and the second probability is above a probability threshold.

7. 发明授权

US11341188B2 Expert stance classification using computerized text analytics 有权
公开(公告)号：US11341188B2
公开(公告)日：2022-05-24
申请号：US16454083
申请日：2019-06-27
申请人： International Business Machines Corporation
发明人： Roy Bar-Haim , Noam Slonim , Orith Toledo-Ronen
IPC分类号： G06F16/00 , G06F16/9032 , G06F16/955 , G06F40/284 , G06F40/295 , G06F16/31 , G06F16/33 , G06F40/30 , G06F40/134 , G06V30/413
摘要： A computerized text analysis method that comprises: searching a resource of information with a search query comprising at least one of: (a) the specific debatable topic, and (b) a personal derivation of the specific debatable topic, to obtain a list of indices whose index subject contains the personal derivation and/or the specific debatable topic; determining, by applying a rule-based classifier, whether the index subject of each of the indices is (i) in favor of the debatable topic or (ii) against the debatable topic; detecting, in each of the indices, hyperlinks to encyclopedic entries whose entry subjects are person names; and determining that: if the index subject of each of the one or more indices is in favor of the specific debatable topic, then the persons are in favor of the specific debatable topic, and vice versa.

8. 发明授权

US11308419B2 Learning sentiment composition from sentiment lexicons 有权
公开(公告)号：US11308419B2
公开(公告)日：2022-04-19
申请号：US16191478
申请日：2018-11-15
申请人： International Business Machines Corporation
发明人： Ranit Aharonov , Roy Bar-Haim , Alon Halfon , Charles Arthur Jochim , Amir Menczel , Noam Slonim , Orith Toledo-Ronen
IPC分类号： G06N20/00 , G06F17/18 , G06F40/30 , G06F40/284
摘要： A method including: generating, from a text corpus, a lexicon of unigrams and bigrams comprising an embedding for each of said unigrams and bigrams; training a machine learning classifier on a training set comprising a subset of said lexicon, wherein each of said unigrams and bigrams in said subset has a sentiment label; applying said machine learning classifier to said lexicon, to (i) predict a sentiment of each of said unigrams and bigrams, and (ii) update said lexicon with the predicted sentiments; and performing statistical analysis on said updated lexicon, to extract one or more sentiment composition lexicons, wherein each of said one or more sentiment composition lexicons is associated with a sentiment composition class.

9. 发明授权

US10509895B2 Biometric authentication 有权
公开(公告)号：US10509895B2
公开(公告)日：2019-12-17
申请号：US15064632
申请日：2016-03-09
申请人： International Business Machines Corporation
发明人： Hagai Aronowitz , Amir Geva , Ron Hoory , David Nahamoo , Jason William Pelecanos , Orith Toledo-Ronen
IPC分类号： G06F21/32 , G06K9/00 , G06N20/00 , G06K9/62
摘要： A method comprising using at least one hardware processor for: providing a set of development supervectors representing features of biometric samples of multiple subjects, the biometric samples being of at least a first and a second different biometric modalities; providing at least a first and a second enrollment supervectors representing features of at least a first and a second enrollment biometric samples of a target subject correspondingly, wherein the at least first and second enrollment samples are of the at least first and the second different biometric modalities correspondingly; providing at least a first and a second verification supervectors representing features of at least a first and a second verification biometric samples of the target subject correspondingly, wherein the at least first and second verification samples are of the at least first and second different biometric modalities correspondingly; concatenating the development supervectors to a set of development generic supervector, the at least first and second enrollment supervectors to a single enrollment generic supervector and the at least first and second verification supervectors to a single verification generic supervector; and verifying an identity of the target subject based on a fused score calculated for the verification generic supervector, wherein the fused score is calculated based on the enrollment generic supervector and the set of development generic supervectors.

10. 发明授权

US10387472B2 Expert stance classification using computerized text analytics 有权
公开(公告)号：US10387472B2
公开(公告)日：2019-08-20
申请号：US15453918
申请日：2017-03-09
申请人： International Business Machines Corporation
发明人： Roy Bar-Haim , Noam Slonim , Orith Toledo-Ronen
IPC分类号： G06F16/00 , G06F16/35 , G06F16/31 , G06F16/93 , G06F16/33 , G06F16/955 , G06F17/27
摘要： A computerized text analysis method that comprises: searching a resource of information with a search query comprising at least one of: (a) the specific debatable topic, and (b) a personal derivation of the specific debatable topic, to obtain a list of indices whose index subject contains the personal derivation and/or the specific debatable topic; determining, by applying a rule-based classifier, whether the index subject of each of the indices is (i) in favor of the debatable topic or (ii) against the debatable topic; detecting, in each of the indices, hyperlinks to encyclopedic entries whose entry subjects are person names; and determining that: if the index subject of each of the one or more indices is in favor of the specific debatable topic, then the persons are in favor of the specific debatable topic, and vice versa.

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