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    • 51. 发明申请
    • METHOD AND SYSTEM TO IMPROVE AUTOMATED EMOTIONAL RECOGNITION
    • 提高自动情感识别的方法与系统
    • WO2008092474A1
    • 2008-08-07
    • PCT/EP2007/000816
    • 2007-01-31
    • TELECOM ITALIA S.P.A.BOLLANO, GianmarioETTORRE, DonatoESILIATO, Antonio
    • BOLLANO, GianmarioETTORRE, DonatoESILIATO, Antonio
    • G10L17/00
    • G10L17/26
    • An automated emotional recognition system (100) is provided. The emotional recognition system comprises an emotional state classifier (110) adapted to receive, during an operative phase, an input information stream (SD) with embedded information related to emotional states of a person, and to generate a succession of emotional state indications (SES) derived from said input information stream. The emotional recognition system further comprises a post-processing function (120), configured to receive at least two emotional state indications of said succession and, for each of said at least two emotional state indications, determine a corresponding emotional state representation in an emotional state representation system. The post-processing function is further configured to combine the emotional state representations of said at least two emotional state indications to obtain an output emotional state indication (OES).
    • 提供自动情感识别系统(100)。 情绪识别系统包括情绪状态分类器(110),其适于在操作阶段期间接收具有与人的情绪状态相关的嵌入信息的输入信息流(SD),并且产生一系列情绪状态指示(SES )从所述输入信息流导出。 情绪识别系统还包括后处理功能(120),其被配置为接收所述继承的至少两个情感状态指示,并且对于所述至少两个情绪状态指示中的每个,确定情绪状态中的相应情绪状态表示 代表制度。 后处理功能还被配置为组合所述至少两个情绪状态指示的情绪状态表示以获得输出情绪状态指示(OES)。
    • 52. 发明申请
    • CUSTOMIZABLE METHOD AND SYSTEM FOR EMOTIONAL RECOGNITION
    • 用于情感识别的自定义方法和系统
    • WO2008092473A1
    • 2008-08-07
    • PCT/EP2007/000815
    • 2007-01-31
    • TELECOM ITALIA S.P.A.BOLLANO, GianmarioETTORRE, DonatoESILIATO, Antonio
    • BOLLANO, GianmarioETTORRE, DonatoESILIATO, Antonio
    • G10L15/06G10L15/28G10L17/00
    • G10L15/065G10L15/30G10L17/26
    • An automated emotional recognition system (100; 100a; 100b) is provided. The automated emotional recognition system is adapted to determine emotional states of a speaker based on the analysis of a speech signal (SS). The emotional recognition system comprises at least one server function (110; 110a; 110b) and at least one client function (120; 120a; 120b) in communication with the at least one server function for receiving assistance in the determining the emotional states of the speaker. The at least one client function includes an emotional features calculator (215) adapted to receive the speech signal (SS) and to extract therefrom a set of speech features (SF) indicative of the emotional state of the speaker. The emotional state recognition system further includes at least one emotional state decider (235; 705) adapted to determine the emotional state of the speaker exploiting the set of speech features based on a decision model (MODj; CMOD). The server function includes at least a decision model trainer (237; 735, 740) adapted to update the selected decision model according to the speech signal. The decision model to be used by the emotional state decider for determining the emotional state of the speaker is selectable based on a context of use of the recognition system.
    • 提供自动情感识别系统(100; 100a; 100b)。 自动情绪识别系统适于基于对语音信号(SS)的分析来确定说话者的情绪状态。 所述情绪识别系统包括与所述至少一个服务器功能通信的至少一个服务器功能(110; 110a; 110b)和至少一个客户端功能(120; 120a; 120b),用于在确定所述服务器功能 扬声器。 所述至少一个客户端功能包括适于接收所述语音信号(SS)的情绪特征计算器(215)并从中提取指示所述说话者的情感状态的一组语音特征(SF)。 所述情绪状态识别系统还包括至少一个情绪状态判定器(235; 705),其适于基于决策模型(MODj; CMOD)来确定利用所述一组语音特征的所述扬声器的情绪状态。 服务器功能至少包括适合于根据语音信号更新所选择的决策模型的决策模型训练器(237; 735,740)。 情绪状态决定者用于确定说话者的情感状态的决定模型是基于使用识别系统的上下文来选择的。
    • 53. 发明申请
    • METHOD AND SYSTEM FOR BIOMETRIC AUTHENTICATION AND ENCRYPTION
    • 用于生物识别和加密的方法和系统
    • WO2008080414A1
    • 2008-07-10
    • PCT/EP2006/012562
    • 2006-12-28
    • TELECOM ITALIA S.P.A.GOLIC, JovanBALTATU, Madalina
    • GOLIC, JovanBALTATU, Madalina
    • H04L9/32
    • H04L9/0866G06K9/00288G07C9/00158H04L9/3231H04L2209/08H04L2209/34
    • Disclosed herein is a biometric user authentication method, comprising enrolling a user based on user's biometric samples to generate user's reference data; and authenticating the user based on a user's live biometric sample and the user's reference data; wherein enrolling a user includes acquiring the user's biometric samples; extracting an enrollment feature vector (x j ) from each user's biometric sample; computing a biometric reference template vector as a mean vector (x) based on the enrollment feature vectors (x j ); computing a variation vector (g) based on the enrollment feature vectors (x j ) and the mean vector (x); randomly generating an enrollment secret vector (s); computing an enrollment code vector (z) based on the enrollment secret vector (s) and the variation vector (g); computing a difference vector (w) as a wrap-around difference between the enrollment code vector (z) and the mean vector (x); computing an error correction vector (p) based on the enrollment secret vector (s) to enable error correction during the user authentication phase according to a given error tolerance level (e), wherein the error correction vector is not computed if the error tolerance level is equal to zero; and storing the variation vector (q), the difference vector (w), and the error correction vector (p) as a part of the user's reference data to be used during the user authentication phase.
    • 本文公开了一种生物特征用户认证方法,包括基于用户的生物特征样本登记用户以生成用户的参考数据; 以及基于用户的实时生物特征样本和用户的参考数据来认证用户; 其中登记用户包括获取所述用户的生物特征样本; 从每个用户的生物测定样本中提取注册特征向量(x∈J); 基于所述注册特征向量(x> j),将生物测定参考模板向量计算为平均向量(x); 基于所述注册特征向量(x N j)和所述平均向量(x)计算变量向量(g); 随机生成登记秘密向量; 基于所述登记秘密向量和所述变化向量(g)计算登记码矢量(z); 将差分矢量(w)计算为注册码矢量(z)和平均矢量(x)之间的环绕差; 基于所述注册秘密向量来计算纠错向量(p),以在根据给定的误差容许度(e)的用户认证阶段期间能够进行纠错,其中如果误差容限等级 等于零; 并将变化矢量(q),差矢量(w)和误差校正矢量(p)存储为在用户认证阶段期间要使用的用户参考数据的一部分。