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1. 发明申请

US20080319929A1 Automated Action-Selection System and Method , and Application Thereof to Training Prediction Machines and Driving the Development of Self-Developing Devices 有权
标题翻译：自动化行动选择系统及方法及其应用，用于培训预测机器，推动自主研发设备的发展
公开(公告)号：US20080319929A1
公开(公告)日：2008-12-25
申请号：US11658683
申请日：2005-07-26
申请人： Frederic Kaplan , Pierre-Yves Oudeyer
发明人： Frederic Kaplan , Pierre-Yves Oudeyer
IPC分类号： G06F15/18
CPC分类号： G06N3/004
摘要： In order to promote efficient learning of relationships inherent in a system or setup S described by system-state and context parameters, the next action to take, affecting the setup, is determined based on the knowledge gain expected to result from this action. Knowledge-gain is assessed “locally” by comparing the value of a knowledge-indicator parameter after the action with the value of this indicator on one or more previous occasions when the system-state/context parameter(s) and action variable(s)=had similar values to the current ones. Preferably the “level of knowledge” is assessed based on the accuracy of predictions made by a prediction module. This technique can be applied to train a prediction machine by causing it to participate in the selection of a sequence of actions. This technique can also be applied for managing development of a self-developing device or system, the self-developing device or system performing a sequence of actions selected according to the action-selection technique.
摘要翻译：为了促进由系统状态和上下文参数描述的系统或设备S固有的关系的有效学习，基于预期从该动作产生的知识增益来确定影响设置的下一个动作。通过将系统状态/上下文参数和动作变量（一个或多个）的一个或多个以前场合的一个或多个先前场合的动作后面的知识指标参数的值与该指标的值进行比较来评估知识增益， =具有与当前值相似的值。优选地，基于预测模块进行的预测的准确性来评估“知识水平”。该技术可以应用于通过使预测机器参与动作序列的选择来训练预测机器。该技术还可以用于管理自我开发设备或系统的开发，该自我开发设备或系统执行根据动作选择技术选择的一系列动作。

2. 发明授权

US07412390B2 Method and apparatus for speech synthesis, program, recording medium, method and apparatus for generating constraint information and robot apparatus 失效
标题翻译：用于语音合成的方法和装置，程序，记录介质，用于产生约束信息的方法和装置以及机器人装置
公开(公告)号：US07412390B2
公开(公告)日：2008-08-12
申请号：US10387659
申请日：2003-03-13
申请人： Erika Kobayashi , Toshiyuki Kumakura , Makoto Akabane , Kenichiro Kobayashi , Nobuhide Yamazaki , Tomoaki Nitta , Pierre Yves Oudeyer
发明人： Erika Kobayashi , Toshiyuki Kumakura , Makoto Akabane , Kenichiro Kobayashi , Nobuhide Yamazaki , Tomoaki Nitta , Pierre Yves Oudeyer
IPC分类号： G10L13/00 , G10L13/06
CPC分类号： G10L13/02 , G10L13/04
摘要： The emotion is to be added to the synthesized speech as the prosodic feature of the language is maintained. In a speech synthesis device 200, a language processor 201 generates a string of pronunciation marks from the text, and a prosodic data generating unit 202 creates prosodic data, expressing the time duration, pitch, sound volume or the like parameters of phonemes, based on the string of pronunciation marks. A constraint information generating unit 203 is fed with the prosodic data and with the string of pronunciation marks to generate the constraint information which limits the changes in the parameters to add the so generated constraint information to the prosodic data. A emotion filter 204, fed with the prosodic data, to which has been added the constraint information, changes the parameters of the prosodic data, within the constraint, responsive to the feeling state information, imparted to it. A waveform generating unit 205 synthesizes the speech waveform based on the prosodic data the parameters of which have been changed.
摘要翻译：情感将被添加到合成语音中，因为语言的韵律特征得到维持。在语音合成装置200中，语言处理部201从文本生成一串发音标记，韵律数据生成部202基于音韵数据生成韵律数据，表示音素的持续时间，音调，音量等参数，基于字符串的发音标记。约束信息生成单元203被馈送有韵律数据和发音标记串，以产生限制参数变化的约束信息，以将如此生成的约束信息添加到韵律数据。响应于赋予它的感觉状态信息，馈送有已经添加了约束信息的韵律数据的情绪滤波器204在约束内改变韵律数据的参数。波形生成单元205基于其参数已被改变的韵律数据来合成语音波形。

3. 发明申请

US20050021483A1 Architecture for self-developing devices 有权
标题翻译：自主研发设备的架构
公开(公告)号：US20050021483A1
公开(公告)日：2005-01-27
申请号：US10861146
申请日：2004-06-04
申请人： Frederic Kaplan , Pierre-Yves Oudeyer
发明人： Frederic Kaplan , Pierre-Yves Oudeyer
IPC分类号： B25J13/00 , G06N3/00 , G06F15/18
CPC分类号： G06N3/004
摘要： A self-developing device (1) capable of open-ended development makes use of a special motivational system for selecting which action should be taken on the environment by an associated sensory-motor apparatus (2). For a given candidate action, a motivational module (11) calculates a reward associated with the corresponding values that would be taken by one or more motivational variables that are independent of the nature of the associated sensory-motor apparatus. Preferred motivational variables are dependent on the developmental history of the device (1), and include variables quantifying the predictability, familiarity and stability of sensory-motor variables serving as the inputs to the device (1). The sensory-motor variables represent the status of the external environment and/or the internal resources (3) of the sensory-motor apparatus (2) whose behaviour is controlled by the self-developing device (1). Open-ended development is enabled by attributing a reward which is proportional to the rate of change of the history-dependent motivational variables.
摘要翻译：能够进行开放式开发的自行开发装置（1）利用特殊的激励系统，用于通过相关的感官电动机装置（2）选择对环境采取的动作。对于给定的候选动作，激励模块（11）计算与由与相关联的感觉运动装置的性质无关的一个或多个动机变量所采取的对应值相关联的奖励。优选的动机变量取决于设备的发展历史（1），并且包括量化作为设备输入的感觉运动变量的可预测性，熟悉度和稳定性的变量（1）。感官运动变量表示由自我开发装置（1）控制其行为的感觉运动装置（2）的外部环境和/或内部资源（3）的状态。通过归纳与历史相关的动机变量的变化率成正比的奖励来实现开放式开发。

4. 发明授权

US06760645B2 Training of autonomous robots 失效
标题翻译：自主机器人训练
公开(公告)号：US06760645B2
公开(公告)日：2004-07-06
申请号：US10134909
申请日：2002-04-29
申请人： Frédéric Kaplan , Pierre-Yves Oudeyer
发明人： Frédéric Kaplan , Pierre-Yves Oudeyer
IPC分类号： G05B1900
CPC分类号： A63H11/00 , A63H2200/00
摘要： A clicker-training technique developed for animal training is adapted for training robots, notably autonomous animal-like robots. In this robot-training method, a behaviour (for example, (DIG)) is broken down into smaller achievable responses ((SIT)-(HELLO)-(DIG)) that will eventually lead to the desired final behaviour. The robot is guided progressively to the correct behaviour through the use, normally the repeated use, of a secondary reinforcer. When the correct behaviour has been achieved, a primary reinforcer is applied so that the desired behaviour can be “captured”. This method can be used for training a robot to perform, on command, rare behaviours or a sequence of behaviours (typically actions). This method can also be used to ensure that a robot is focusing its attention upon a desired object.
摘要翻译：针对动物训练开发的点击训练技术适用于训练机器人，特别是自主动物类机器人。在这种机器人训练方法中，行为（例如，（DIG））被分解成较小的可实现的响应（（SIT） - （HELLO） - （DIG）），这将最终导致期望的最终行为。机器人通过次级加强件的使用（通常是重复使用）逐步引导到正确的行为。当已经实现正确的行为时，应用主加强件，以便可以“捕获”所需的行为。这种方法可以用于训练机器人来执行命令，罕见行为或一系列行为（通常是动作）。该方法也可用于确保机器人将注意力集中在所需物体上。

5. 发明授权

US07672913B2 Automated action-selection system and method, and application thereof to training prediction machines and driving the development of self-developing devices 有权
标题翻译：自动动作选择系统及方法及其应用于训练预测机器，推动自主研发设备的发展
公开(公告)号：US07672913B2
公开(公告)日：2010-03-02
申请号：US11658683
申请日：2005-07-26
申请人： Frederic Kaplan , Pierre-Yves Oudeyer
发明人： Frederic Kaplan , Pierre-Yves Oudeyer
IPC分类号： G06N5/00
CPC分类号： G06N3/004
摘要： In order to promote efficient learning of relationships inherent in a system or setup S described by system-state and context parameters, the next action to take, affecting the setup, is determined based on the knowledge gain expected to result from this action. Knowledge-gain is assessed “locally” by comparing the value of a knowledge-indicator parameter after the action with the value of this indicator on one or more previous occasions when the system-state/context parameter(s) and action variable(s) had similar values to the current ones. Preferably the “level of knowledge” is assessed based on the accuracy of predictions made by a prediction module. This technique can be applied to train a prediction machine by causing it to participate in the selection of a sequence of actions. This technique can also be applied for managing development of a self-developing device or system, the self-developing device or system performing a sequence of actions selected according to the action-selection technique.
摘要翻译：为了促进由系统状态和上下文参数描述的系统或设备S固有的关系的有效学习，基于预期从该动作产生的知识增益来确定影响设置的下一个动作。通过将系统状态/上下文参数和动作变量（一个或多个）的一个或多个以前场合的一个或多个以上场合比较，将动作后的知识指标参数的值与该指标的值进行比较来评估知识增益，具有与当前值相似的值。优选地，基于预测模块进行的预测的准确性来评估“知识水平”。该技术可以应用于通过使预测机器参与动作序列的选择来训练预测机器。该技术还可以用于管理自我开发设备或系统的开发，该自我开发设备或系统执行根据动作选择技术选择的一系列动作。

6. 发明授权

US07478073B2 Architecture for self-developing devices 有权
标题翻译：自主研发设备的架构
公开(公告)号：US07478073B2
公开(公告)日：2009-01-13
申请号：US10861146
申请日：2004-06-04
申请人： Frederic Kaplan , Pierre-Yves Oudeyer
发明人： Frederic Kaplan , Pierre-Yves Oudeyer
IPC分类号： G06F15/18 , G05B13/00
CPC分类号： G06N3/004
摘要： A self-developing device (1) capable of open-ended development makes use of a special motivational system for selecting which action should be taken on the environment by an associated sensory-motor apparatus (2). For a given candidate action, a motivational module (11) calculates a reward associated with the corresponding values that would be taken by one or more motivational variables that are independent of the nature of the associated sensory-motor apparatus. Preferred motivational variables are dependent on the developmental history of the device (1), and include variables quantifying the predictability, familiarity and stability of sensory-motor variables serving as the inputs to the device (1). The sensory-motor variables represent the status of the external environment and/or the internal resources (3) of the sensory-motor apparatus (2) whose behavior is controlled by the self-developing device (1). Open-ended development is enabled by attributing a reward which is proportional to the rate of change of the history-dependent motivational variables.
摘要翻译：能够进行开放式开发的自行开发装置（1）利用特殊的激励系统，用于通过相关的感官电动机装置（2）选择对环境采取的动作。对于给定的候选动作，激励模块（11）计算与由与相关联的感觉运动装置的性质无关的一个或多个动机变量所采取的对应值相关联的奖励。优选的动机变量取决于设备的发展历史（1），并且包括量化作为设备输入的感觉运动变量的可预测性，熟悉度和稳定性的变量（1）。感官运动变量表示由自我开发装置（1）控制其行为的感觉运动装置（2）的外部环境和/或内部资源（3）的状态。通过归纳与历史相关的动机变量的变化率成正比的奖励来实现开放式开发。

7. 发明授权

US07457752B2 Method and apparatus for controlling the operation of an emotion synthesizing device 失效
标题翻译：用于控制情感合成装置的操作的方法和装置
公开(公告)号：US07457752B2
公开(公告)日：2008-11-25
申请号：US10217002
申请日：2002-08-12
申请人： Pierre Yves Oudeyer
发明人： Pierre Yves Oudeyer
IPC分类号： G10L13/00
CPC分类号： G10L13/033 , G10L13/10
摘要： Method and apparatus for controlling the operation of an emotion synthesizing device, notably of the type where the emotion is conveyed by a sound, having at least one input parameter whose value is used to set a type of emotion to be conveyed, by making at least one parameter a variable parameter over a determined control range, thereby to confer a variability in an amount of the type of emotion to be conveyed. The variable parameter can be made variable according to a variation model over the control range, the model relating a quantity of emotion control variable to the variable parameter, whereby said control variable is used to variably establish a value of said variable parameter. Preferably the variation obeys a linear model, the variable parameter being made to vary linearly with a variation in a quantity of emotion control variable.
摘要翻译：用于控制情绪合成装置的操作的方法和装置，特别是通过声音传达情感的类型，具有至少一个输入参数，其值用于设置要传达的情感的类型，至少通过至少一个参数是在确定的控制范围上的可变参数，从而赋予要传达的情感类型的量的可变性。可变参数可以根据控制范围上的变化模型变化，该模型将情绪控制变量的数量与可变参数相关联，由此所述控制变量用于可变地建立所述可变参数的值。优选地，变化遵守线性模型，使可变参数随着情绪控制变量的变化而线性变化。

8. 发明授权

US07451079B2 Emotion recognition method and device 失效
标题翻译：情感识别方法及装置
公开(公告)号：US07451079B2
公开(公告)日：2008-11-11
申请号：US10194848
申请日：2002-07-12
申请人： Pierre-Yves Oudeyer
发明人： Pierre-Yves Oudeyer
IPC分类号： G10L21/06 , G10L11/04
CPC分类号： G10L13/033 , G10L13/00 , G10L13/04 , G10L13/10 , G10L17/26
摘要： Emotion recognition is performed by extracting a set comprising at least one feature derived from a signal, and processing the set of extracted feature(s) to detect an emotion therefrom. The voice signal is low pass filtered prior to extracting therefrom at least one feature of the set. The cut-off frequency for the low pass filtering is typically centered around 250 Hz. The features are e.g. statistical quantities extracted from sampling a signal of the intensity or pitch of the voice signal.
摘要翻译：通过提取包括从信号导出的至少一个特征的集合并且处理所提取的特征集合来检测情感来执行情感识别。语音信号在从中提取该集合的至少一个特征之前被低通滤波。低通滤波的截止频率通常以250Hz为中心。特征是例如。从对语音信号的强度或音调的信号进行采样提取的统计量。

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