公开(公告)号：US20090190899A1

公开(公告)日：2009-07-30

申请号：US12019786

申请日：2008-01-25

Applicant: Srinivas BANGALORE

Inventor： Srinivas BANGALORE

IPC: H04N5/00

CPC classification number: G06F17/30796 ,  G09B21/006 ,  G10L15/26 ,  H04N21/4394 ,  H04N21/440236 ,  H04N21/4828 ,  H04N21/8547

Abstract: Disclosed are systems, methods, and computer readable media for retrieving digital images. The method embodiment includes converting a descriptive audio stream of a digital video that is provided for the visually impaired to text and then aligning that text to the appropriate segment of the digital video. The system then indexes the converted text from the descriptive audio stream with the text's relationship to the digital video. The system enables queries using action words describing a desired scene from a digital video.

Abstract translation: 公开了用于检索数字图像的系统，方法和计算机可读介质。 方法实施例包括将为视障者提供的数字视频的描述性音频流转换为文本，然后将该文本对准数字视频的适当段。 然后系统将文本与数字视频的关系从描述性音频流索引转换后的文本。 该系统使用从数字视频描述所需场景的动作词来查询。

公开(公告)号：US20110145224A1

公开(公告)日：2011-06-16

申请号：US12638570

申请日：2009-12-15

Applicant: Srinivas BANGALORE

Inventor： Srinivas BANGALORE

IPC: G06F17/30

CPC classification number: G06F17/30684 ,  G06F17/30864 ,  G06F17/30976 ,  G10L15/26 ,  G10L15/265

Abstract: Disclosed herein are systems, methods, and computer-readable storage media for receiving a user's spoken search query that the system will incrementally recognize and identify search terms. After the query has been incrementally recognized, the system will use the search terms to retrieve a portion of the search results that are based on usable identified search terms. As the results are found, the system will then output at least part at least part of the retrieved portion of search results on the display prior to the user concluding his or her search query.

Abstract translation: 本文公开了用于接收用户的口语搜索查询的系统，方法和计算机可读存储介质，系统将逐步识别和识别搜索项。 在逐渐识别查询之后，系统将使用搜索项来检索基于可用的识别搜索项的搜索结果的一部分。 当搜索结果被发现时，系统将在用户结束他或她的搜索查询之前在显示器上输出至少部分被检索的搜索结果部分的部分。

公开(公告)号：US20100217580A1

公开(公告)日：2010-08-26

申请号：US12772580

申请日：2010-05-03

Applicant: Srinivas BANGALORE ,  David Crawford GIBBON ,  Mazin GILBERT ,  Patrick Guy HAFFNER ,  Zhu LIU ,  Behzad SHAHRARAY

Inventor： Srinivas BANGALORE ,  David Crawford GIBBON ,  Mazin GILBERT ,  Patrick Guy HAFFNER ,  Zhu LIU ,  Behzad SHAHRARAY

IPC: G06F17/28

CPC classification number: H04N21/4856 ,  G06F17/289 ,  G10L21/10 ,  H04N7/0885 ,  H04N7/17336 ,  H04N21/2355 ,  H04N21/2543 ,  H04N21/25435 ,  H04N21/4355 ,  H04N21/440236 ,  H04N21/4882 ,  H04N21/4884 ,  H04N21/8193

Abstract: A method, a system and a machine-readable medium are provided for an on demand translation service. A translation module including at least one language pair module for translating a source language to a target language may be made available for use by a subscriber. The subscriber may be charged a fee for use of the requested on demand translation service or may be provided use of the on demand translation service for free in exchange for displaying commercial messages to the subscriber. A video signal may be received including information in the source language, which may be obtained as text from the video signal and may be translated from the source language to the target language by use of the translation module. Translated information, based on the translated text, may be added into the received video signal. The video signal including the translated information in the target language may be sent to a display device.

Abstract translation: 为按需翻译服务提供方法，系统和机器可读介质。 包括用于将源语言翻译成目标语言的至少一个语言对模块的翻译模块可以被用户使用。 用户可能会收取使用所请求的按需翻译服务的费用，或者可以免费使用按需翻译服务，以便向用户显示商业消息。 可以接收包括源语言的信息的视频信号，其可以从视频信号获取为文本，并且可以通过使用翻译模块从源语言翻译成目标语言。 基于翻译文本的翻译信息可以被添加到接收的视频信号中。 可以将包括目标语言的翻译信息的视频信号发送到显示装置。

公开(公告)号：US20090192781A1

公开(公告)日：2009-07-30

申请号：US12022819

申请日：2008-01-30

Applicant: Srinivas BANGALORE ,  Emil Ettelaie

Inventor： Srinivas BANGALORE ,  Emil Ettelaie

IPC: G06F17/28

CPC classification number: G06F17/2827

Abstract: A machine translation method, system for using the method, and computer readable media are disclosed. The method includes the steps of receiving a source language sentence, selecting a set of target language n-grams using a lexical classifier and based on the source language sentence. When selecting the set of target language n-grams, in at least one n-gram, n is greater than 1. The method continues by combining the selected set of target language n-grams as a finite state acceptor (FSA), weighting the FSA with data from the lexical classifier, and generating an n-best list of target sentences from the FSA. As an alternate to using the FSA, N strings may be generated from the n-grams and ranked using a language model. The N strings may be represented by an FSA for efficiency but it is not necessary.

Abstract translation: 公开了一种机器翻译方法，使用该方法的系统和计算机可读介质。 该方法包括以下步骤：接收源语言句，使用词法分类器并基于源语言句选择一组目标语言n-gram。 当选择一组目标语言n-gram时，在至少一个n-gram中，n大于1.该方法通过将所选择的一组目标语言n-gram组合为有限状态接收器（FSA）来继续加权， FSA与来自词汇分类器的数据，并从FSA生成目标句子的最佳列表。 作为使用FSA的替代方案，可以使用n-gram生成N个字符串，并使用语言模型进行排序。 N字符串可以由FSA表示以提高效率，但不是必需的。

公开(公告)号：US20120232885A1

公开(公告)日：2012-09-13

申请号：US13042890

申请日：2011-03-08

Applicant: Luciano De Andrade BARBOSA ,  Srinivas BANGALORE

Inventor： Luciano De Andrade BARBOSA ,  Srinivas BANGALORE

IPC: G06F17/27 ,  G10L15/00

CPC classification number: G06F17/28 ,  G06F17/21 ,  G06F17/27 ,  G06F17/2705 ,  G06F17/2715 ,  G06F17/2735 ,  G06F17/2765 ,  G10L2015/0633

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for collecting web data in order to create diverse language models. A system configured to practice the method first crawls, such as via a crawler operating on a computing device, a set of documents in a network of interconnected devices according to a visitation policy, wherein the visitation policy is configured to focus on novelty regions for a current language model built from previous crawling cycles by crawling documents whose vocabulary considered likely to fill gaps in the current language model. A language model from a previous cycle can be used to guide the creation of a language model in the following cycle. The novelty regions can include documents with high perplexity values over the current language model.

Abstract translation: 本文公开了用于收集网络数据以便创建不同语言模型的系统，方法和非暂时的计算机可读存储介质。 被配置为实践该方法的系统首先通过根据访问策略的互连设备的网络中的诸如通过在计算设备上操作的爬行器来爬行一组文档，其中所述访问策略被配置为专注于新颖区域 目前的语言模型是从以前的爬行周期构建的，通过抓取其词汇被认为可能填补当前语言模型的空白的文档。 来自上一个循环的语言模型可用于指导在以下循环中创建语言模型。 新奇区域可以包括与当前语言模型相比具有高困惑价值的文档。

公开(公告)号：US20120095861A1

公开(公告)日：2012-04-19

申请号：US12905172

申请日：2010-10-15

Applicant: Junlan FENG ,  Srinivas BANGALORE ,  Michael James Robert JOHNSTON ,  Taniya MISHRA

Inventor： Junlan FENG ,  Srinivas BANGALORE ,  Michael James Robert JOHNSTON ,  Taniya MISHRA

IPC: G06Q30/00 ,  G06Q10/00 ,  G10L15/26 ,  G06F15/173

CPC classification number: G06F17/30345 ,  G06Q10/00 ,  G06Q30/00 ,  G06Q30/014 ,  G06Q30/0282 ,  G06Q30/04 ,  G06Q30/0601 ,  G06Q30/0631 ,  H04L67/22 ,  H04L67/306

Abstract: Aggregating information includes configuring, by at least one processor, a user profile that indicates user preferences for aggregated information. The at least one processor monitors information sources including the World Wide Web, business websites of interest, and online social media, based on the user preferences. Data obtained from the information sources is presented, based on the monitoring, by the at least one processor, in accordance with a presentation format, as the aggregated information, based on the user preferences. The at least one processor triggers updating of the presented aggregated information based on a change to the data at least one of the information sources and a change to the user profile.

Abstract translation: 聚合信息包括由至少一个处理器配置指示聚合信息的用户偏好的用户简档。 至少一个处理器基于用户偏好来监视包括万维网，感兴趣的商业网站和在线社交媒体的信息源。 基于信息源获得的数据，基于由至少一个处理器根据用户偏好根据呈现格式作为聚合信息的监视来呈现。 所述至少一个处理器基于对所述数据的至少一个信息源的改变以及对所述用户简档的改变来触发对所呈现的聚合信息的更新。

公开(公告)号：US20110144995A1

公开(公告)日：2011-06-16

申请号：US12638649

申请日：2009-12-15

Applicant: Srinivas BANGALORE ,  Taniya MISHRA

Inventor： Srinivas BANGALORE ,  Taniya MISHRA

IPC: G10L15/00 ,  G06F17/30

CPC classification number: G10L15/18 ,  G06F17/30637 ,  G06F17/30663 ,  G10L15/083

Abstract: Disclosed herein are systems, methods, and computer-readable storage media for performing a search. A system configured to practice the method first receives from an automatic speech recognition (ASR) system a word lattice based on speech query and receives indexed documents from an information repository. The system composes, based on the word lattice and the indexed documents, at least one triple including a query word, selected indexed document, and weight. The system generates an N-best path through the word lattice based on the at least one triple and re-ranks ASR output based on the N-best path. The system aggregates each weight across the query words to generate N-best listings and returns search results to the speech query based on the re-ranked ASR output and the N-best listings. The lattice can be a confusion network, the arc density of which can be adjusted for a desired performance level.

Abstract translation: 本文公开了用于执行搜索的系统，方法和计算机可读存储介质。 配置为实施该方法的系统首先从自动语音识别（ASR）系统接收基于语音查询的字格，并从信息库接收索引的文档。 该系统基于字格和索引文档，组合至少一个包括查询词，选择的索引文档和权重的三元组。 该系统基于至少一个三重生成通过该字格的N个最佳路径，并且基于该N最佳路径重新排列ASR输出。 系统通过查询字聚合每个权重，以产生N最佳列表，并根据重新排列的ASR输出和N最佳列表将搜索结果返回给语音查询。 晶格可以是混淆网络，其电弧密度可以针对期望的性能水平进行调整。

公开(公告)号：US20100082326A1

公开(公告)日：2010-04-01

申请号：US12241660

申请日：2008-09-30

Applicant: Srinivas BANGALORE ,  Vivek Kumar Rangarajan Sridhar

Inventor： Srinivas BANGALORE ,  Vivek Kumar Rangarajan Sridhar

IPC: G06F17/28

CPC classification number: G06F17/289 ,  G10L13/10

Abstract: Disclosed herein are systems, methods, and computer readable-media for enriching spoken language translation with prosodic information in a statistical speech translation framework. The method includes receiving speech for translation to a target language, generating pitch accent labels representing segments of the received speech which are prosodically prominent, and injecting pitch accent labels with word tokens within the translation engine to create enriched target language output text. A further step may be added of synthesizing speech in the target language based on the prosody enriched target language output text. An automatic prosody labeler can generate pitch accent labels. An automatic prosody labeler can exploit lexical, syntactic, and prosodic information of the speech. A maximum entropy model may be used to determine which segments of the speech are prosodically prominent. A pitch accent label can include an indication of certainty that a respective segment of the speech is prosodically prominent and/or an indication of prosodic prominence of a respective segment of speech.

Abstract translation: 本文公开了用于在统计语音翻译框架中丰富口头语言翻译与韵律信息的系统，方法和计算机可读介质。 该方法包括接收用于翻译到目标语言的语音，产生表示接收到的语音段的韵律突出的音调重音标签，以及在翻译引擎内用词令牌注入音调重音标签，以创建丰富的目标语言输出文本。 可以基于韵律丰富的目标语言输出文本，添加目标语言中的合成语音的另一步骤。 自动韵律贴标机可以产生音调重音标签。 自动韵律标签者可以利用言语的词汇，句法和韵律信息。 可以使用最大熵模型来确定语音的哪些段韵律突出。 音调重音标签可以包括确定语音的相应片段韵律突出的指示和/或相应语音段的韵律突出的指示。