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1. 发明授权

US08505053B2 User interface having reading lens 有权
标题翻译：具有读取镜头的用户界面
公开(公告)号：US08505053B2
公开(公告)日：2013-08-06
申请号：US13458276
申请日：2012-04-27
申请人： Stephen Glennon , Steve Johnson , Stephen Buck , Peter F. Brown
发明人： Stephen Glennon , Steve Johnson , Stephen Buck , Peter F. Brown
IPC分类号： H04N5/445
CPC分类号： H04N21/482 , H04N5/4403 , H04N21/4314 , H04N21/4821
摘要： A user interface, such as a graphical user interface or other electronic displayable interface, is contemplated. The user interface may include a reading lens portion configured to facilitate providing expanded viewing of content from other portions of the display. The reading lens portion may be displayed according to a non-linear timeline as to facilitate identifying upcoming contents without being constrained by a linear timeline used in other portions of the user interface.
摘要翻译：可以想到诸如图形用户界面或其他电子可显示界面的用户界面。用户接口可以包括被配置为便于从显示器的其他部分提供对内容的扩展观看的读取透镜部分。可以根据非线性时间线来显示读取透镜部分，以便于识别即将到来的内容，而不受用户界面的其他部分中使用的线性时间轴的约束。

2. 发明申请

US20120278840A1 USER INTERFACE HAVING READING LENS 有权
标题翻译：具有读取镜头的用户界面
公开(公告)号：US20120278840A1
公开(公告)日：2012-11-01
申请号：US13458276
申请日：2012-04-27
申请人： Stephen Glennon , Steve Johnson , Stephen Buck , Peter F. Brown
发明人： Stephen Glennon , Steve Johnson , Stephen Buck , Peter F. Brown
IPC分类号： H04N21/482
CPC分类号： H04N21/482 , H04N5/4403 , H04N21/4314 , H04N21/4821
摘要： A user interface, such as a graphical user interface or other electronic displayable interface, is contemplated. The user interface may include a reading lens portion configured to facilitate providing expanded viewing of content from other portions of the display. The reading lens portion may be displayed according to a non-linear timeline as to facilitate identifying upcoming contents without being constrained by a linear timeline used in other portions of the user interface.
摘要翻译：可以想到诸如图形用户界面或其他电子可显示界面的用户界面。用户接口可以包括被配置为便于从显示器的其他部分提供对内容的扩展观看的读取透镜部分。可以根据非线性时间线来显示读取透镜部分，以便于识别即将到来的内容，而不受用户界面的其他部分中使用的线性时间轴的约束。

3. 发明授权

US5483102A Employing on die temperature sensors and fan-heatsink failure signals to control power dissipation 失效
标题翻译：使用模具温度传感器和风扇散热器故障信号来控制功耗
公开(公告)号：US5483102A
公开(公告)日：1996-01-09
申请号：US241777
申请日：1994-05-12
申请人： James R. Neal , Peter F. Brown , Louis W. Agatstein , Michael Gutman
发明人： James R. Neal , Peter F. Brown , Louis W. Agatstein , Michael Gutman
IPC分类号： G06F1/20 , G06F1/32 , G06F15/20
CPC分类号： G06F1/3215 , G06F1/206 , G06F1/324 , H01L2224/48091 , H01L2224/48227 , H01L2224/49109 , H01L2924/15322 , H01L2924/16195 , Y02B60/1217 , Y02B60/1275
摘要： A circuit and method for reducing an internal clocking frequency of the semiconductor device upon receiving a first signal indicating that a fan element disposed on the semiconductor device is operating at an unacceptable performance level and/or a second signal indicating that the semiconductor device is operating at a temperature greater than a prescribed boundary temperature.
摘要翻译：一种用于在接收到指示设置在半导体器件上的风扇元件处于不可接受的性能水平的第一信号和/或指示半导体器件正在操作的第二信号时减小半导体器件的内部时钟频率的电路和方法温度大于规定的边界温度。

4. 发明授权

US5477451A Method and system for natural language translation 失效
标题翻译：自然语言翻译方法与系统
公开(公告)号：US5477451A
公开(公告)日：1995-12-19
申请号：US736278
申请日：1991-07-25
申请人： Peter F. Brown , John Cocke , Stephen A. Della Pietra , Vincent J. Della Pietra , Frederick Jelinek , Jennifer C. Lai , Robert L. Mercer
发明人： Peter F. Brown , John Cocke , Stephen A. Della Pietra , Vincent J. Della Pietra , Frederick Jelinek , Jennifer C. Lai , Robert L. Mercer
IPC分类号： G10L15/14 , G06F17/27 , G06F17/28 , G10L15/00 , G06F17/20
CPC分类号： G06F17/2818 , G06F17/2755 , G06F17/2845 , G06F17/2872
摘要： The present invention is a system for translating text from a first source language into a second target language. The system assigns probabilities or scores to various target-language translations and then displays or makes otherwise available the highest scoring translations. The source text is first transduced into one or more intermediate structural representations. From these intermediate source structures a set of intermediate target-structure hypotheses is generated. These hypotheses are scored by two different models: a language model which assigns a probability or score to an intermediate target structure, and a translation model which assigns a probability or score to the event that an intermediate target structure is translated into an intermediate source structure. Scores from the translation model and language model are combined into a combined score for each intermediate target-structure hypothesis. Finally, a set of target-text hypotheses is produced by transducing the highest scoring target-structure hypotheses into portions of text in the target language. The system can either run in batch mode, in which case it translates source-language text into a target language without human assistance, or it can function as an aid to a human translator. When functioning as an aid to a human translator, the human may simply select from the various translation hypotheses provided by the system, or he may optionally provide hints or constraints on how to perform one or more of the stages of source transduction, hypothesis generation and target transduction.
摘要翻译：本发明是用于将文本从第一源语言翻译成第二目标语言的系统。系统将概率或分数分配给各种目标语言翻译，然后显示或使其他可用的最高得分翻译。源文本首先被转换成一个或多个中间结构表示。从这些中间源结构生成一组中间目标结构假设。这些假设用两种不同的模型进行评分：将中间目标结构分配概率或分数的语言模型，以及将中间目标结构转换为中间源结构的事件分配概率或分数的翻译模型。翻译模型和语言模型的得分被组合为每个中间目标结构假说的综合得分。最后，通过将目标语言文本的最高得分目标结构假设转换为部分文本来产生一组目标文本假设。该系统可以以批处理模式运行，在这种情况下，它将源语言文本转换为目标语言，而无需人工帮助，或者可以作为人类翻译器的辅助功能。人类可以简单地从系统提供的各种翻译假设中进行选择，或者可选择地提供关于如何执行源转换，假设生成的一个或多个阶段的提示或限制，靶转导。

5. 发明授权

US4852173A Design and construction of a binary-tree system for language modelling 失效
标题翻译：用于语言建模的二叉树系统的设计和构造
公开(公告)号：US4852173A
公开(公告)日：1989-07-25
申请号：US114892
申请日：1987-10-29
申请人： Lalit R. Bahl , Peter F. Brown , Peter V. deSouza , Robert L. Mercer
发明人： Lalit R. Bahl , Peter F. Brown , Peter V. deSouza , Robert L. Mercer
IPC分类号： G10L11/00 , G06F15/18 , G06F17/18 , G10L15/00 , G10L15/10 , G10L15/18
CPC分类号： G06N99/005 , G06F17/18 , G10L15/00
摘要： In order to determine a next event based upon available data, a binary decision tree is constructed having true or false questions at each node and a probability distribution of the unknown next event based upon available data at each leaf. Starting at the root of the tree, the construction process proceeds from node-to-node towards a leaf by answering the question at each node encountered and following either the true or false path depending upon the answer. The questions are phrased in terms of the available data and are designed to provide as much information as possible about the next unknown event. The process is particularly useful in speech recognition when the next word to be spoken is determined on the basis of the previously spoken words.
摘要翻译：为了基于可用数据确定下一个事件，构建在每个节点处具有真或假问题的二进制决策树，以及基于每个叶片处的可用数据的未知下一事件的概率分布。从树的根开始，构建过程通过回答所遇到的每个节点的问题，并根据答案遵循真实或错误的路径，从节点到节点进行到叶。这些问题是根据可用数据编写的，旨在为下一个未知事件提供尽可能多的信息。当基于先前说出的单词确定要说出的下一个单词时，该过程特别有用。

6. 发明授权

US4718093A Speech recognition method including biased principal components 失效
标题翻译：语音识别方法包括偏向主成分
公开(公告)号：US4718093A
公开(公告)日：1988-01-05
申请号：US593894
申请日：1984-03-27
申请人： Peter F. Brown
发明人： Peter F. Brown
IPC分类号： G10L15/00 , G10L5/00
CPC分类号： G10L15/00
摘要： A speech recognition method and apparatus employ a speech processing circuitry for repetitively deriving from a speech input, at a frame repetition rate, a plurality of acoustic parameters. The acoustic parameters represent the speech input signal for a frame time. A plurality of template matching and cost processing circuitries are connected to a system bus, along with the speech processing circuitry, for determining, or identifying, the speech units in the input speech, by comparing the acoustic parameters with stored template patterns. The apparatus can be expanded by adding more template matching and cost processing circuitry to the bus thereby increasing the speech recognition capacity of the apparatus. The speech processing circuitry establishes overlapping time durations for generating the acoustic parameters and further employs a sinc-Kaiser smoothing function in combination with a folding technique for providing a discrete Fourier transform. The Fourier spectra are transformed using a biased principal component analysis which optimizes the across class variance. The template matching and cost processing circuitries provide distributed processing, on demand, of the acoustic parameters for generating through a dynamic programming technique the recognition decision.
摘要翻译：语音识别方法和装置采用语音处理电路，以帧重复率重复地从语音输入中导出多个声学参数。声学参数表示帧时间的语音输入信号。通过将声学参数与存储的模板图案进行比较，多个模板匹配和成本处理电路连同语音处理电路连接到用于确定或识别输入语音中的语音单元的系统总线。可以通过向总线添加更多的模板匹配和成本处理电路来扩展该装置，从而增加装置的语音识别能力。语音处理电路建立用于产生声学参数的重叠时间持续时间，并且还结合用于提供离散傅里叶变换的折叠技术，采用sinc-Kaiser平滑函数。傅立叶光谱使用偏置主成分分析进行变换，该分析优化了跨类别方差。模板匹配和成本处理电路提供分布式处理，根据需要通过动态规划技术生成的声学参数进行识别决策。

7. 发明授权

US5510981A Language translation apparatus and method using context-based translation models 失效
标题翻译：使用基于上下文的翻译模型的语言翻译设备和方法
公开(公告)号：US5510981A
公开(公告)日：1996-04-23
申请号：US144913
申请日：1993-10-28
申请人： Adam L. Berger , Peter F. Brown , Stephen A. Della Pietra , Vincent J. Della Pietra , Andrew S. Kehler , Robert L. Mercer
发明人： Adam L. Berger , Peter F. Brown , Stephen A. Della Pietra , Vincent J. Della Pietra , Andrew S. Kehler , Robert L. Mercer
IPC分类号： G06F17/28
CPC分类号： G06F17/2818 , G06F17/2827
摘要： An apparatus for translating a series of source words in a first language to a series of target words in a second language. For an input series of source words, at least two target hypotheses, each including a series of target words, are generated. Each target word has a context comprising at least one other word in the target hypothesis. For each target hypothesis, a language model match score including an estimate of the probability of occurrence of the series of words in the target hypothesis. At least one alignment connecting each source word with at least one target word in the target hypothesis is identified. For each source word and each target hypothesis, a word match score including an estimate of the conditional probability of occurrence of the source word, given the target word in the target hypothesis which is connected to the source word and given the context in the target hypothesis of the target word which is connected to the source word. For each target hypothesis, a translation match score including a combination of the word match scores for the target hypothesis and the source words in the input series of source words. A target hypothesis match score including a combination of the language model match score for the target hypothesis and the translation match score for the target hypothesis. The target hypothesis having the best target hypothesis match score is output.
摘要翻译：一种用于将第一语言的一系列源词翻译为第二语言的一系列目标词的装置。对于一个输入序列的源字，产生至少两个目标假设，每个包含一系列目标词。每个目标词具有包含目标假设中的至少一个其他单词的上下文。对于每个目标假设，语言模型匹配得分，包括目标假设中的一系列单词的发生概率的估计。识别将每个源字与目标假设中的至少一个目标字连接的至少一个对齐。对于每个源词和每个目标假设，给出包括源词出现的条件概率的估计的词匹配分数，给出连接到源词并且给定目标假设的上下文的目标假设中的目标词连接到源字的目标字。对于每个目标假设，翻译匹配分数包括目标假设的词匹配分数与输入源词序列中的源词组合。目标假设匹配得分，包括目标假设的语言模型匹配分数与目标假设的翻译匹配得分的组合。输出具有最佳目标假设匹配得分的目标假设。

8. 发明授权

US5033087A Method and apparatus for the automatic determination of phonological rules as for a continuous speech recognition system 失效
标题翻译：用于连续语音识别系统自动确定语音规则的方法和装置
公开(公告)号：US5033087A
公开(公告)日：1991-07-16
申请号：US323479
申请日：1989-03-14
申请人： Lalit R. Bahl , Peter F. Brown , Peter V. DeSouza , Robert L. Mercer
发明人： Lalit R. Bahl , Peter F. Brown , Peter V. DeSouza , Robert L. Mercer
IPC分类号： G10L11/00 , G10L15/06 , G10L15/14
CPC分类号： G10L15/14
摘要： A continuous speech recognition system includes an automatic phonological rules generator which determines variations in the pronunciation of phonemes based on the context in which they occur. This phonological rules generator associates sequences of labels derived from vocalizations of a training text with respective phonemes inferred from the training text. These sequences are then annotated with their pheneme context from the training text and clustered into groups representing similar pronunciations of each phoneme. A decision tree is generated using the context information of the sequences to predict the clusters to which the sequences belong. The training data is processed by the decision tree to divide the sequences into leaf-groups representing similar pronunciations of each phoneme. The sequences in each leaf-group are clustered into sub-groups representing respectively different pronunciations of their corresponding phoneme in a give context. A Markov model is generated for each sub-group. The various Markov models of a leaf-group are combined into a single compound model by assigning common initial and final states to each model. The compound Markov models are used by a speech recognition system to analyze an unknown sequence of labels given its context.

9. 发明授权

US4827521A Training of markov models used in a speech recognition system 失效
标题翻译：在语音识别系统中使用的马尔科夫模型的训练
公开(公告)号：US4827521A
公开(公告)日：1989-05-02
申请号：US845201
申请日：1986-03-27
申请人： Lalit R. Bahl , Peter F. Brown , Peter V. deSouza , Robert L. Mercer
发明人： Lalit R. Bahl , Peter F. Brown , Peter V. deSouza , Robert L. Mercer
IPC分类号： G10L11/00 , G10L15/14 , G10L5/00
CPC分类号： G10L15/14
摘要： In a word, or speech, recognition system for decoding a vocabulary word from outputs selected from an alphabet of outputs in response to a communicated word input wherein each word in the vocabulary is represented by a baseform of at least one probabilistic finite state model and wherein each probabilistic model has transition probability items and output probability items and wherein a value is stored for each of at least some probability items, the present invention relates to apparatus and method for determining probability values for probability items by biassing at least some of the stored values to enhance the likelihood that outputs generated in response to communication of a known word input are produced by the baseform for the known word relative to the respective likelihood of the generated outputs being produced by the baseform for at least one other word. Specifically, the current values of counts --from which probability items are derived--are adjusted by uttering a known word and determining how often probability events occur relative to (a) the model corresponding to the known uttered "correct" word and (b) the model of at least one other "incorrect" word. The current count values are increased based on the event occurrences relating to the correct word and are reduced based on the event occurrences relating to the incorrect word or words.

10. 发明授权

US5293584A Speech recognition system for natural language translation 失效
标题翻译：自然语言翻译语音识别系统
公开(公告)号：US5293584A
公开(公告)日：1994-03-08
申请号：US887205
申请日：1992-05-21
申请人： Peter F. Brown , Stephen A. Della Pietra , Vincent J. Della Pietra , Frederick Jelinek , Robert L. Mercer
发明人： Peter F. Brown , Stephen A. Della Pietra , Vincent J. Della Pietra , Frederick Jelinek , Robert L. Mercer
IPC分类号： G10L15/18 , G10L5/00
CPC分类号： G10L15/18
摘要： A speech recognition system displays a source text of one or more words in a source language. The system has an acoustic processor for generating a sequence of coded representations of an utterance to be recognized. The utterance comprises a series of one or more words in a target language different from the source language. A set of one or more speech hypotheses, each comprising one or more words from the target language, are produced. Each speech hypothesis is modeled with an acoustic model. An acoustic match score for each speech hypothesis comprises an estimate of the closeness of a match between the acoustic model of the speech hypothesis and the sequence of coded representations of the utterance. A translation match score for each speech hypothesis comprises an estimate of the probability of occurrence of the speech hypothesis given the occurrence of the source text. A hypothesis score for each hypothesis comprises a combination of the acoustic match score and the translation match score. At least one word of one or more speech hypotThis invention was made with Government support under Contract Number N00014-91-C-0135 awarded by the office of Naval Research. The Government has certain rights in this invention.
摘要翻译：语音识别系统以源语言显示一个或多个单词的源文本。该系统具有声学处理器，用于产生要识别的话语的编码表示序列。话语包括与源语言不同的目标语言中的一系列一个或多个单词。产生一组一个或多个语音假设，每个语音假设包括来自目标语言的一个或多个单词。每个言语假说都用声学模型建模。每个语音假设的声匹配分数包括语音假设的声学模型与语音的编码表示序列之间的匹配的接近度的估计。每个语音假设的翻译匹配分数包括给定源文本的出现的语音假设的发生概率的估计。每个假设的假设得分包括声匹配分数和翻译匹配分数的组合。输出具有最佳假设得分的一个或多个语音假设的至少一个字作为识别结果。

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