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1.发明授权Eigenvoice re-estimation technique of acoustic models for speech recognition, speaker identification and speaker verification 有权用于语音识别，扬声器识别和说话人验证的声学模型的本征语重新估计技术公开(公告)号：US06895376B2
公开(公告)日：2005-05-17
申请号：US09849174
申请日：2001-05-04
摘要： A reduced dimensionality eigenvoice analytical technique is used during training to develop context-dependent acoustic models for allophones. Re-estimation processes are performed to more strongly separate speaker-dependent and speaker-independent components of the speech model. The eigenvoice technique is also used during run time upon the speech of a new speaker. The technique removes individual speaker idiosyncrasies, to produce more universally applicable and robust allophone models. In one embodiment the eigenvoice technique is used to identify the centroid of each speaker, which may then be “subtracted out” of the recognition equation.
摘要翻译： 在训练期间使用减小的维度本征语音分析技术来开发用于异音素的上下文相关的声学模型。 执行重新估计过程以更强烈地分离语音模型的与扬声器相关的和与扬声器无关的组件。 特定语音技术在运行时也用于新演讲者的演讲。 该技术可以消除单个扬声器的特性，从而产生更普遍适用和强大的异音模型。 在一个实施例中，本征语音技术用于识别每个说话者的质心，然后可以将其“减去”识别方程。
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公开(公告)号：US06970820B2
公开(公告)日：2005-11-29
申请号：US09792928
申请日：2001-02-26
CPC分类号： G10L13/04 , G10L2021/0135
摘要： The speech synthesizer is personalized to sound like or mimic the speech characteristics of an individual speaker. The individual speaker provides a quantity of enrollment data, which can be extracted from a short quantity of speech, and the system modifies the base synthesis parameters to more closely resemble those of the new speaker. More specifically, the synthesis parameters may be decomposed into speaker dependent parameters, such as context-independent parameters, and speaker independent parameters, such as context dependent parameters. The speaker dependent parameters are adapted using enrollment data from the new speaker. After adaptation, the speaker dependent parameters are combined with the speaker independent parameters to provide a set of personalized synthesis parameters. To adapt the parameters with a small amount of enrollment data, an eigenspace is constructed and used to constrain the position of the new speaker so that context independent parameters not provided by the new speaker may be estimated.
摘要翻译： 语音合成器被个性化以发音或模仿单个扬声器的语音特征。 单个扬声器提供一定数量的登记数据，其可以从短语言中提取，并且系统将基本合成参数修改为更接近于新说话者的参考数据。 更具体地，合成参数可以被分解为与扬声器相关的参数，诸如与上下文无关的参数，以及与扬声器无关的参数，诸如与上下文相关的参数。 使用来自新扬声器的注册数据来调整与扬声器相关的参数。 在适应之后，将扬声器依赖参数与扬声器独立参数组合以提供一组个性化合成参数。 为了使参数具有少量的注册数据，构造本征空间并用于约束新的说话者的位置，以便可以估计不能由新发言者提供的上下文独立参数。
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3.发明授权Maximum likelihood method for finding an adapted speaker model in eigenvoice space 失效在本征语音空间中找到适应的说话者模型的最大似然法公开(公告)号：US06263309B1
公开(公告)日：2001-07-17
申请号：US09070054
申请日：1998-04-30
申请人： Patrick Nguyen , Roland Kuhn , Jean-Claude Junqua
发明人： Patrick Nguyen , Roland Kuhn , Jean-Claude Junqua
IPC分类号： G10L1508
CPC分类号： G10L15/07
摘要： A set of speaker dependent models is trained upon a comparatively large number of training speakers, one model per speaker, and model parameters are extracted in a predefined order to construct a set of supervectors, one per speaker. Principle component analysis is then performed on the set of supervectors to generate a set of eigenvectors that define an eigenvoice space. If desired, the number of vectors may be reduced to achieve data compression. Thereafter, a new speaker provides adaptation data from which a supervector is constructed by constraining this supervector to be in the eigenvoice space based on a maximum likelihood estimation. The resulting coefficients in the eigenspace of this new speaker may then be used to construct a new set of model parameters from which an adapted model is constructed for that speaker. Environmental adaptation may be performed by including environmental variations in the training data.
摘要翻译： 一组扬声器依赖模型训练在相对较多数量的训练扬声器上，每个扬声器一个模型和模型参数以预定义的顺序提取，以构建一组超级矢量，每个扬声器一个。 然后在一组超级矢量上执行原理分量分析，以生成一组定义本征语音空间的特征向量。 如果需要，可以减少向量的数量以实现数据压缩。 此后，新的说话者提供了通过基于最大似然估计将该超向量限制在本征语音空间中来构建超向量的适配数据。 然后，可以使用这个新的说话者的本征空间中得到的系数来构建一组新的模型参数，从该模型参数构建适合于该说话者的适应模型。 可以通过在训练数据中包括环境变化来执行环境适应。
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4.发明授权公开(公告)号：US06697778B1
公开(公告)日：2004-02-24
申请号：US09610495
申请日：2000-07-05
申请人： Roland Kuhn , Olivier Thyes , Patrick Nguyen , Jean-Claude Junqua , Robert Boman
发明人： Roland Kuhn , Olivier Thyes , Patrick Nguyen , Jean-Claude Junqua , Robert Boman
IPC分类号： G10L1506
CPC分类号： G10L17/02
摘要： Client speaker locations in a speaker space are used to generate speech models for comparison with test speaker data or test speaker speech models. The speaker space can be constructed using training speakers that are entirely separate from the population of client speakers, or from client speakers, or from a mix of training and client speakers. Reestimation of the speaker space based on client environment information is also provided to improve the likelihood that the client data will fall within the speaker space. During enrollment of the clients into the speaker space, additional client speech can be obtained when predetermined conditions are met. The speaker distribution can also be used in the client enrollment step.
摘要翻译： 扬声器空间中的客户扬声器位置用于产生用于与测试扬声器数据或测试扬声器语音模型进行比较的语音模型。 扬声器空间可以使用与客户端扬声器或客户端扬声器完全分开的训练扬声器，或者由训练和客户端扬声器组合构成。 还提供了基于客户端环境信息对扬声器空间的再估计，以提高客户端数据落入扬声器空间的可能性。 在将客户登记到扬声器空间中，当满足预定条件时，可以获得额外的客户端语音。 扬声器分配也可以在客户端注册步骤中使用。
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5.发明授权Dimensionality reduction for speaker normalization and speaker and environment adaptation using eigenvoice techniques 有权使用本征语音技术的扬声器归一化和扬声器和环境适应的尺寸减小公开(公告)号：US06343267B1
公开(公告)日：2002-01-29
申请号：US09148753
申请日：1998-09-04
申请人： Roland Kuhn , Patrick Nguyen , Jean-Claude Junqua
发明人： Roland Kuhn , Patrick Nguyen , Jean-Claude Junqua
IPC分类号： G10L1908
CPC分类号： G06K9/6247 , G10L15/07
摘要： A set of speaker dependent models or adapted models is trained upon a comparatively large number of training speakers, one model per speaker, and model parameters are extracted in a predefined order to construct a set of supervectors, one per speaker. Dimensionality reduction is then performed on the set of supervectors to generate a set of eigenvectors that define an eigenvoice space. If desired, the number of vectors may be reduced to achieve data compression. Thereafter, a new speaker provides adaptation data from which a supervector is constructed by constraining this supervector to be in the eigenvoice space based on a maximum likelihood estimation. The resulting coefficients in the eigenspace of this new speaker may then be used to construct a new set of model parameters from which an adapted model is constructed for that speaker. The adapted model may then be further adapted via MAP, MLLR, MLED or the like. The eigenvoice technique may be applied to MLLR transformation matrices or the like; Bayesian estimation performed in eigenspace uses prior knowledge about speaker space density to refine the estimate about the location of a new speaker in eigenspace.
摘要翻译： 一组扬声器依赖模型或适应模型被训练在相对较多数量的训练扬声器上，每个扬声器一个模型和模型参数以预定义的顺序被提取以构造一组超级矢量，每个扬声器一个。 然后对该一组超级矢量执行尺寸减小，以生成一组定义本征语音空间的特征向量。 如果需要，可以减少向量的数量以实现数据压缩。 此后，新的说话者提供了通过基于最大似然估计将该超向量限制在本征语音空间中来构建超向量的适配数据。 然后，可以使用这个新的说话者的本征空间中得到的系数来构建一组新的模型参数，从该模型参数构建适合于该说话者的适应模型。 然后可以通过MAP，MLLR，MLED等进一步适配适配模型。 本征语音技术可以应用于MLLR变换矩阵等; 在本体空间中执行的贝叶斯估计使用关于扬声器空间密度的先前知识来改进关于本征空间中新的说话者位置的估计。
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公开(公告)号：US6141644A
公开(公告)日：2000-10-31
申请号：US148911
申请日：1998-09-04
申请人： Roland Kuhn , Patrick Nguyen , Jean-Claude Junqua , Robert Boman
发明人： Roland Kuhn , Patrick Nguyen , Jean-Claude Junqua , Robert Boman
CPC分类号： G10L17/02
摘要： Speech models are constructed and trained upon the speech of known client speakers (and also impostor speakers, in the case of speaker verification). Parameters from these models are concatenated to define supervectors and a linear transformation upon these supervectors results in a dimensionality reduction yielding a low-dimensional space called eigenspace. The training speakers are then represented as points or distributions in eigenspace. Thereafter, new speech data from the test speaker is placed into eigenspace through a similar linear transformation and the proximity in eigenspace of the test speaker to the training speakers serves to authenticate or identify the test speaker.
摘要翻译： 语音模型根据已知的客户端扬声器的语音进行构建和训练（并且在演讲人验证的情况下也引用了演讲者）。 来自这些模型的参数被连接以定义超级向量，并且这些超向量的线性变换导致维度降低，产生称为本征空间的低维空间。 培训演讲者随后被表示为本土空间的分数或分布。 此后，来自测试扬声器的新的语音数据通过类似的线性变换被放置到本征空间中，并且测试扬声器的本征空间与训练扬声器的接近度用于认证或识别测试扬声器。
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7.发明授权公开(公告)号：US06901364B2
公开(公告)日：2005-05-31
申请号：US09951093
申请日：2001-09-13
申请人： Patrick Nguyen , Luca Rigazio , Jean-Claude Junqua
发明人： Patrick Nguyen , Luca Rigazio , Jean-Claude Junqua
CPC分类号： G10L15/1815 , G10L15/30
摘要： An e-mail message process is provided for use with a personal digital assistant which allows for the use of input speech messaging which is converted to text using a focused language model which is downloaded by a cellular phone connection to an Internet server which provides the focused language model based upon a topic for the intended e-mail message. The text that is generated from the input speech method can be summarized by the e-mail message processor and can be edited by the user. The generated e-mail message can then be transmitted again via cellular connection to an Internet e-mail server for transmitting the e-mail message to a recipient.
摘要翻译： 提供电子邮件消息处理以与个人数字助理一起使用，该个人数字助理允许使用输入语音消息传送，其使用由通过蜂窝电话连接下载的聚焦语言模型转换为文本，该互联网服务器提供聚焦 基于预期电子邮件的主题的语言模型。 从输入语音方法生成的文本可以由电子邮件消息处理器来总结，并且可以由用户编辑。 然后可以通过蜂窝连接再次将生成的电子邮件消息发送到Internet电子邮件服务器，以将电子邮件消息发送给接收者。
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公开(公告)号：US07089182B2
公开(公告)日：2006-08-08
申请号：US10099305
申请日：2002-03-15
IPC分类号： G10L15/20
CPC分类号： G10L15/20 , G10L15/02 , G10L15/063 , G10L21/0216
摘要： A method for performing noise adaptation of a target speech signal input to a speech recognition system, where the target speech signal contains both additive and convolutional noises. The method includes estimating an additive noise bias and a convolutional noise bias; in the target speech signal; and jointly compensating the target speech signal for the additive and convolutional noise biases in a feature domain.
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公开(公告)号：US20050228663A1
公开(公告)日：2005-10-13
申请号：US10814960
申请日：2004-03-31
申请人： Robert Boman , Patrick Nguyen , Jean-Claude Junqua
发明人： Robert Boman , Patrick Nguyen , Jean-Claude Junqua
IPC分类号： G10L15/26
CPC分类号： G10L15/26
摘要： A media production system includes a textual alignment module aligning multiple speech recordings to textual lines of a script based on speech recognition results. A navigation module responds to user navigation selections respective of the textual lines of the script by communicating to the user corresponding, line-specific portions of the multiple speech recordings. An editing module responds to user associations of multiple speech recordings with textual lines by accumulating line-specific portions of the multiple speech recordings in a combination recording based on at least one of relationships of textual lines in the script to the combination recording, and temporal alignments between the multiple speech recordings and the combination recording.
摘要翻译： 媒体制作系统包括文本对准模块，其基于语音识别结果将多个语音记录与脚本的文本行对齐。 导航模块通过与用户对应的多个语音记录的线特定部分通信来响应相应于脚本的文本行的用户导航选择。 编辑模块通过基于脚本中的文本行的关系与组合记录中的至少一种相结合记录来组合记录中的多个语音记录的行特定部分来累积多个语音记录与文本行的响应，以及时间对齐 在多个语音记录和组合记录之间。
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公开(公告)号：US06272462B1
公开(公告)日：2001-08-07
申请号：US09257893
申请日：1999-02-25
IPC分类号： G10L1506
CPC分类号： G10L15/075 , G10L2015/0635
摘要： Supervised adaptation speech is supplied to the recognizer and the recognizer generates the N-best transcriptions of the adaptation speech. These transcriptions include the one transcription known to be correct, based on a priori knowledge of the adaptation speech, and the remaining transcriptions known to be incorrect. The system applies weights to each transcription: a positive weight to the correct transcription and negative weights to the incorrect transcriptions. These weights have the effect of moving the incorrect transcriptions away from the correct one, rendering the recognition system more discriminative for the new speaker's speaking characteristics. Weights applied to the incorrect solutions are based on the respective likelihood scores generated by the recognizer. The sum of all weights (positive and negative) are a positive number. This ensures that the system will converge.
摘要翻译： 受监督的适应语音被提供给识别器，并且识别器生成适应语音的N个最佳的转录。 这些转录包括基于适应言语的先验知识的已知正确的一个转录，以及已知不正确的剩余转录。 该系统对每个转录应用权重：对正确转录的正负重和不正确转录的负权重。 这些权重具有将错误的记录从正确的转录中移开的效果，使识别系统对于新的说话者的说话特征更具歧视性。 应用于不正确解的权重是基于识别器产生的各自的可能性得分。 所有权重（正和负）的和是正数。 这样可以确保系统收敛。
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