公开(公告)号：US20060067548A1

公开(公告)日：2006-03-30

申请号：US11274013

申请日：2005-11-14

申请人： Malcolm Slaney ,  Michele Covell ,  Steven Saunders

发明人： Malcolm Slaney ,  Michele Covell ,  Steven Saunders

IPC分类号： H04R5/02

CPC分类号： H04S1/002 ,  H04S2420/01

摘要： The estimation of an HRTF for a given individual is accomplished by means of a coupled model, which identifies the dependencies between one or more images of readily observable characteristics of an individual, and the HRTF that is applicable to that individual. Since the HRTF is highly influenced by the shape of the listener's outer ear, as well as the shape of the listener's head, images of a listener which provides this type of information are preferably applied as an input to the coupled model. In addition, dimensional measurements of the listener can be applied to the model. In return, the model provides an estimate of the HRTF for the observed characteristics of the listener.

摘要翻译： 对于给定个体的HRTF的估计是通过耦合模型来实现的，该模型识别个体容易观察到的特征的一个或多个图像与适用于该个体的HRTF之间的依赖关系。 由于HRTF受到听众的外耳的形状以及听众头部的形状的高度影响，所以提供这种类型的信息的收听者的图像优选地被应用于耦合模型的输入。 另外，听众的尺寸测量可以应用于模型。 作为回报，该模型提供了对于观察者的观察特征的HRTF的估计。

公开(公告)号：US06400828B2

公开(公告)日：2002-06-04

申请号：US09781229

申请日：2001-02-13

申请人： Michele Covell ,  Malcolm Slaney

发明人： Michele Covell ,  Malcolm Slaney

IPC分类号： G06K900

CPC分类号： G06K9/00281 ,  G06K9/4609 ,  G06K9/48 ,  G06K9/6211 ,  G06K2009/487

摘要： The identification of hidden data, such as feature-based control points in an image, from a set of observable data, such as the image, is achieved through a two-stage approach. The first stage involves a learning process, in which a number of sample data sets, e.g. images, are analyzed to identify the correspondence between observable data, such as visual aspects of the image, and the desired hidden data, such as the control points. Two models are created. A feature appearance-only model is created from aligned examples of the feature in the observed data. In addition, each labeled data set is processed to generate a coupled model of the aligned observed data and the associated hidden data. In the second stage of the process, the modeled feature is located in an unmarked, unaligned data set, using the feature appearance-only model. This location is used as an alignment point and the coupled model is then applied to the aligned data, giving an estimate of the hidden data values for that data set.

摘要翻译： 通过两阶段方法，可以从一组可观察数据（如图像）中识别隐藏数据，如图像中基于特征的控制点。 第一阶段涉及学习过程，其中多个样本数据集，例如， 分析图像以识别诸如图像的视觉方面的可观察数据与期望的隐藏数据（例如控制点）之间的对应关系。 创建了两个模型。 仅从观察数据中的特征的对齐示例创建仅出现特征的模型。 此外，处理每个标记的数据集以生成对准的观察数据和相关联的隐藏数据的耦合模型。 在该过程的第二阶段，建模特征位于未标记的未对齐数据集中，使用仅特征外观模型。 该位置用作对齐点，然后将耦合模型应用于对齐的数据，给出该数据集的隐藏数据值的估计。

公开(公告)号：US07840019B2

公开(公告)日：2010-11-23

申请号：US11274013

申请日：2005-11-14

申请人： Malcolm Slaney ,  Michele Covell ,  Steven E. Saunders

发明人： Malcolm Slaney ,  Michele Covell ,  Steven E. Saunders

IPC分类号： H04R5/02 ,  H04R5/00

CPC分类号： H04S1/002 ,  H04S2420/01

摘要： The estimation of an HRTF for a given individual is accomplished by means of a coupled model, which identifies the dependencies between one or more images of readily observable characteristics of an individual, and the HRTF that is applicable to that individual. Since the HRTF is highly influenced by the shape of the listener's outer ear, as well as the shape of the listener's head, images of a listener which provides this type of information are preferably applied as an input to the coupled model. In addition, dimensional measurements of the listener can be applied to the model. In return, the model provides an estimate of the HRTF for the observed characteristics of the listener.

摘要翻译： 对于给定个体的HRTF的估计是通过耦合模型来实现的，该模型识别个体容易观察到的特征的一个或多个图像与适用于该个体的HRTF之间的依赖关系。 由于HRTF受到听众的外耳的形状以及听众头部的形状的高度影响，所以提供这种类型的信息的收听者的图像优选地被应用于耦合模型的输入。 另外，听众的尺寸测量可以应用于模型。 作为回报，该模型提供了对于观察者的观察特征的HRTF的估计。

公开(公告)号：US06996244B1

公开(公告)日：2006-02-07

申请号：US09369340

申请日：1999-08-06

申请人： Malcolm Slaney ,  Michele Covell ,  Steven E. Saunders

发明人： Malcolm Slaney ,  Michele Covell ,  Steven E. Saunders

IPC分类号： H04R5/02

CPC分类号： H04S1/002 ,  H04S2420/01

摘要： The estimation of an HRTF for a given individual is accomplished by means of a coupled model, which identifies the dependencies between one or more images of readily observable characteristics of an individual, and the HRTF that is applicable to that individual. Since the HRTF is highly influenced by the shape of the listener's outer ear, as well as the shape of the listener's head, images of a listener which provides this type of information are preferably applied as an input to the coupled model. In addition, dimensional measurements of the listener can be applied to the model. In return, the model provides an estimate of the HRTF for the observed characteristics of the listener.

摘要翻译： 对于给定个体的HRTF的估计是通过耦合模型来实现的，该模型识别个体容易观察到的特征的一个或多个图像与适用于该个体的HRTF之间的依赖关系。 由于HRTF受到听众的外耳的形状以及听众头部的形状的高度影响，所以提供这种类型的信息的收听者的图像优选地被应用于耦合模型的输入。 另外，听众的尺寸测量可以应用于模型。 作为回报，该模型提供了对于观察者的观察特征的HRTF的估计。

公开(公告)号：US06628821B1

公开(公告)日：2003-09-30

申请号：US10145580

申请日：2002-05-13

申请人： Michele Covell ,  Malcolm Slaney

发明人： Michele Covell ,  Malcolm Slaney

IPC分类号： G06K962

CPC分类号： G06K9/00281 ,  G06K9/4609 ,  G06K9/48 ,  G06K9/6211 ,  G06K2009/487

摘要： The identification of hidden data, such as feature-based control points in an image, from a set of observable data, such as the image, is achieved through a two-stage approach. The first stage involves a learning process, in which a number of sample data sets, e.g. images, are analyzed to identify the correspondence between observable data, such as visual aspects of the image, and the desired hidden data, such as the control points. Two models are created. A feature appearance-only model is created from aligned examples of the feature in the observed data. In addition, each labeled data set is processed to generate a coupled model of the aligned observed data and the associated hidden data. In the second stage of the process, the modeled feature is located in an unmarked, unaligned data set, using the feature appearance-only model. This location is used as an alignment point and the coupled model is then applied to the aligned data, giving an estimate of the hidden data values for that data set.

公开(公告)号：US20070033057A1

公开(公告)日：2007-02-08

申请号：US11580559

申请日：2006-10-12

申请人： Michele Covell ,  Malcolm Slaney ,  Arthur Rothstein

发明人： Michele Covell ,  Malcolm Slaney ,  Arthur Rothstein

IPC分类号： G10L21/04

CPC分类号： G10L21/04 ,  G10L19/173

摘要： A data-compressed audio waveform is temporally modified without requiring complete decompression of the audio signal. Packets of compressed audio data are first unpacked, to remove scaling that was applied in the formation of the packets. The unpacked data is then temporally modified, using one of a number of different approaches. This modification takes place while the audio information remains in a data-compressed format. New packets are then assembled from the modified data, to produce a data-compressed output stream that can be subsequently processed in a conventional manner to reproduce the desired sound. The assembly of the new packets employs a technique for inferring an auditory model from the original packets, to requantize the data in the output packets.

摘要翻译： 数据压缩音频波形在时间上被修改，而不需要音频信号的完全解压缩。 压缩音频数据的数据包首先被打包，以消除在数据包的形成中应用的缩放。 然后使用多种不同的方法之一来暂时地修改解包的数据。 当音频信息保持数据压缩格式时，进行这种修改。 然后从修改的数据组装新的分组，以产生可以以常规方式随后处理以再现期望的声音的数据压缩输出流。 新分组的组合采用从原始分组推断听觉模型的技术，以重新输出输出分组中的数据。

公开(公告)号：US20050131683A1

公开(公告)日：2005-06-16

申请号：US10944456

申请日：2004-09-17

申请人： Michele Covell ,  Malcolm Slaney ,  Arthur Rothstein

发明人： Michele Covell ,  Malcolm Slaney ,  Arthur Rothstein

IPC分类号： G10L21/04 ,  G10L19/00

CPC分类号： G11B20/00007 ,  G10L21/04 ,  G11B20/10527

摘要： A data-compressed audio waveform is temporally modified without requiring complete decompression of the audio signal. Packets of compressed audio data are first unpacked, to remove scaling that was applied in the formation of the packets. The unpacked data is then temporally modified, using one of a number of different approaches. This modification takes place while the audio information remains in a data-compressed format. New packets are then assembled from the modified data, to produce a data-compressed output stream that can be subsequently processed in a conventional manner to reproduce the desired sound. The assembly of the new packets employs a technique for inferring an auditory model from the original packets, to requantize the data in the output packets.

公开(公告)号：US20130259379A1

公开(公告)日：2013-10-03

申请号：US13434738

申请日：2012-03-29

申请人： Malcolm Slaney ,  Bee-Chung Chen ,  Deepak K. Agarwal

发明人： Malcolm Slaney ,  Bee-Chung Chen ,  Deepak K. Agarwal

IPC分类号： G06K9/46

CPC分类号： G06K9/6263 ,  G06F17/3005 ,  G06F17/30247 ,  G06K9/00677 ,  G06K9/6277

摘要： Software for initialized explore-exploit creates a plurality of probability distributions. Each of these probability distributions is generated by inputting a quantitative description of one or more features associated with an image into a regression model that outputs a probability distribution for a measure of engagingness for the image. Each of the images is conceptually related to the other images. The software uses the plurality of probability distributions to initialize a multi-armed bandit model that outputs a serving scheme for each of the images. Then the software serves a plurality of the images on a web page displaying search results, based at least in part on the serving scheme.

摘要翻译： 用于初始化的探险攻击的软件创建多个概率分布。 通过将与图像相关联的一个或多个特征的定量描述输入到输出图像的接合度的概率分布的回归模型中来生成这些概率分布中的每一个。 每个图像在概念上与其他图像相关。 软件使用多个概率分布来初始化针对每个图像输出服务方案的多武装强盗模型。 然后，至少部分地基于服务方案，软件在显示搜索结果的网页上提供多个图像。

公开(公告)号：US08522274B2

公开(公告)日：2013-08-27

申请号：US13475822

申请日：2012-05-18

申请人： Malcolm Slaney ,  Bonnie M. Johnson ,  Annarosa Tomasai ,  Steven E. Saunders ,  J. Thomas Ngo ,  Gavin Miller ,  Michele M. Covell ,  Paul A. Freiberger

发明人： Malcolm Slaney ,  Bonnie M. Johnson ,  Annarosa Tomasai ,  Steven E. Saunders ,  J. Thomas Ngo ,  Gavin Miller ,  Michele M. Covell ,  Paul A. Freiberger

IPC分类号： H04N7/025 ,  H04N7/16 ,  G06F3/00

CPC分类号： H04N21/458 ,  G06Q30/0241 ,  G06Q30/0269 ,  G06Q30/0276 ,  H04H20/10 ,  H04H60/31 ,  H04H60/33 ,  H04H60/40 ,  H04H60/45 ,  H04H60/65 ,  H04H60/66 ,  H04N5/445 ,  H04N7/163 ,  H04N7/17318 ,  H04N21/234327 ,  H04N21/25866 ,  H04N21/42201 ,  H04N21/42202 ,  H04N21/4223 ,  H04N21/4415 ,  H04N21/44222 ,  H04N21/4532 ,  H04N21/454 ,  H04N21/4621 ,  H04N21/466 ,  H04N21/47205 ,  H04N21/4722 ,  H04N21/4755 ,  H04N21/478 ,  H04N21/4781 ,  H04N21/6582 ,  H04N21/812

摘要： A method for displaying interactive advertisements on a television having a controller connected thereto and configured for receiving input from a viewer of the television is disclosed. The controller has a receiver operable to receive advertisements and a processor operable to modify the advertisements. The method generally comprises requesting action by the viewer of the television, modifying an advertisement based on the action of the viewer, and displaying the modified advertisement on the television.

公开(公告)号：US08407230B2

公开(公告)日：2013-03-26

申请号：US11842899

申请日：2007-08-21

申请人： Malcolm Slaney ,  William White

发明人： Malcolm Slaney ,  William White

IPC分类号： G06F7/00 ,  G06F17/30 ,  G06F17/00

CPC分类号： G06F17/3053 ,  G06F17/30749 ,  G06F17/30752 ,  G06F17/30758 ,  G06F17/30766 ,  G06F17/30772

摘要： The systems and methods described create a mathematical representation of each of the media objects for which user ratings are known. The mathematical representations take into account the subjective rating value assigned by a user to the respective media object and the user that assigned the rating value. The media object with the mathematical representation closest to that of the seed media object is then selected as the most similar media object to the seed media object. In an embodiment, the mathematical representation is a vector representation in which each user is a different dimension and each user's rating value is the magnitude of the vector in that dimension. Similarity between two songs is determined by identifying the closest vectors to that of the seed song. Closeness may be determined by subtracting or by calculating the dot product of each of the vectors with that of the seed media object.

摘要翻译： 所描述的系统和方法创建了用户评级已知的每个媒体对象的数学表示。 数学表示考虑了用户分配给相应媒体对象和分配了评级值的用户的主观评价值。 然后选择具有最接近种子媒体对象的数学表示的媒体对象作为种子媒体对象的最相似的媒体对象。 在一个实施例中，数学表示是向量表示，其中每个用户是不同的维度，并且每个用户的评价值是该维度中的向量的大小。 通过识别与种子歌曲的最接近的向量来确定两首歌曲之间的相似性。 可以通过减去或通过计算每个向量的种子媒体对象的点积来确定亲密度。