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    • 31. 发明授权
    • Web enabled recognition architecture
    • Web启用识别架构
    • US07506022B2
    • 2009-03-17
    • US09960232
    • 2001-09-20
    • Kuansan WangHsiao-Wuen Hon
    • Kuansan WangHsiao-Wuen Hon
    • G06F15/16G10L11/00
    • G10L15/30G06F3/16G06F17/218H04M1/271H04M1/72561H04M3/493H04M3/4936H04M2207/40
    • A server/client system for processing data includes a network having a web server with information accessible remotely. A client device includes a microphone and a rendering component such as a speaker or display. The client device is configured to obtain the information from the web server and record input data associated with fields contained in the information. The client device is adapted to send the input data to a remote location with an indication of a grammar to use for recognition. A recognition server receives the input data and the indication of the grammar. The recognition server returns data indicative of what was recognized to at least one of the client and the web server.
    • 用于处理数据的服务器/客户端系统包括具有Web服务器的网络,其中信息可远程访问。 客户端设备包括麦克风和诸如扬声器或显示器的渲染组件。 客户端设备配置为从Web服务器获取信息并记录与包含在信息中的字段相关联的输入数据。 客户端设备适于将输入数据发送到远程位置,并具有用于识别的语法指示。 识别服务器接收输入数据和语法的指示。 识别服务器返回表示对客户机和web服务器中的至少一个识别的内容的数据。
    • 33. 发明申请
    • Content Object Indexing Using Domain Knowledge
    • 使用域知识的内容对象索引
    • US20070162408A1
    • 2007-07-12
    • US11275509
    • 2006-01-11
    • Wei-Ying MaLie LuJi-Rong WenZhiwei LiZaiqing NieHsiao-Wuen Hon
    • Wei-Ying MaLie LuJi-Rong WenZhiwei LiZaiqing NieHsiao-Wuen Hon
    • G06N5/02
    • G06F17/30613
    • A content object indexing process including creating a content object knowledge index, calculating a description vector of a target content object, and indexing the target content object by searching for the description vector in the content object knowledge database. It may be difficult to search for an exact content object such as a music file or academic researcher as a conventional search index may not include related hierarchical information. A content object indexing process may add hierarchical information taken from a content object knowledge index and incorporate the hierarchical information to the index entry for a specific content object. An application of such a content object indexing process may be a world wide web search engine.
    • 内容对象索引处理包括创建内容对象知识索引,计算目标内容对象的描述向量,并通过搜索内容对象知识库中的描述向量来索引目标内容对象。 可能难以搜索诸如音乐文件或学术研究者的确切内容对象,因为传统的搜索索引可能不包括相关的分层信息。 内容对象索引处理可以添加从内容对象知识索引获取的分层信息,并且将分层信息并入特定内容对象的索引条目。 这样的内容对象索引处理的应用可以是万维网搜索引擎。
    • 36. 发明授权
    • Speech recognition method and apparatus utilizing multi-unit models
    • 使用多单元模型的语音识别方法和装置
    • US06629073B1
    • 2003-09-30
    • US09559505
    • 2000-04-27
    • Hsiao-Wuen HonKuansan Wang
    • Hsiao-Wuen HonKuansan Wang
    • G01L1506
    • G10L15/187G10L2015/022G10L2015/025
    • A speech recognition method and system utilize an acoustic model that is capable of providing probabilities for both a large acoustic unit and an acoustic sub-unit. Each of these probabilities describes the likelihood of a set of feature vectors from a series of feature vectors representing a speech signal. The large acoustic unit is formed from a plurality of acoustic sub-units. At least one sub-unit probability and at least on large unit probability from the acoustic model are used by a decoder to generate a score for a sequence of hypothesized words. When combined, the acoustic sub-units associated with all of the sub-unit probabilities used to determine the score span fewer than all of the feature vectors in the series of feature vectors. An overlapping decoding technique is also provided.
    • 语音识别方法和系统利用能够为大声学单元和声学子单元提供概率的声学模型。 这些概率中的每一个描述了来自表示语音信号的一系列特征向量的一组特征向量的可能性。 大型声学单元由多个声学子单元形成。 解码器使用来自声学模型的至少一个子单元概率和至少基于大的单位概率来为假设词的序列生成分数。 当组合时,与用于确定分数的所有子单元概率相关联的声学子单元小于该系列特征向量中的所有特征向量。 还提供了重叠的解码技术。
    • 37. 发明授权
    • Confidence measure system using a near-miss pattern
    • 使用近似模式的置信度系统
    • US06571210B2
    • 2003-05-27
    • US09192001
    • 1998-11-13
    • Hsiao-Wuen HonAsela J. R. Gunawardana
    • Hsiao-Wuen HonAsela J. R. Gunawardana
    • G10L1506
    • G10L15/08
    • A method and system of performing confidence measure in a speech recognition system includes receiving an utterance of input speech and creating a near-miss pattern or a near-miss list of possible word entries for the utterance. Each word entry includes an associated value of probability that the utterance corresponds to the word entry. The near-miss list of possible word entries is compared with corresponding stored near-miss confidence templates. Each word in the vocabulary (or keyword list) of near-miss confidence template, which includes a list of word entries and each word entry in each list includes an associated value. Confidence measure for a particular hypothesis word is performed based on the comparison of the values in the near-miss list of possible word entries with the values of the corresponding near-miss confidence template.
    • 在语音识别系统中执行置信度测量的方法和系统包括:接收输入语音的发声,并创建用于话语的可能单词条目的接近丢失模式或近似列表。 每个词条目包括发音对应于词条目的概率的相关值。 将可能的词条的近奇列表与相应的存储的近错信度模板进行比较。 近错信号模板的词汇表(或关键字列表)中的每个单词包括一个词条目列表和每个列表中的每个单词条目包括相关联的值。 基于将可能词条近似列表中的值与对应的近错信度模板的值进行比较来执行特定假设词的置信度度量。
    • 39. 发明申请
    • AIR QUALITY INFERENCE USING MULTIPLE DATA SOURCES
    • 使用多个数据源的空气质量控制
    • US20160125307A1
    • 2016-05-05
    • US14896344
    • 2013-06-05
    • Yu ZHENGXing XIEWei-Ying MAHsiao-Wuen HONEric I-Chao CHANGMICROSOFT TECHNOLOGY LICENSING, LLC
    • Yu ZhengXing XieWei-Ying MaHsiao-Wuen HonEric I-Chao Chang
    • G06N7/00G06N3/08G06N99/00
    • G06N7/005G06N3/08G06N20/00
    • The use of data from multiple data source provides inferred air quality indices with respect to a particular pollutant for multiple areas without the addition of air quality monitor stations to those areas. Labeled air quality index data for a pollutant in a region may be obtained from one or more air quality monitor stations. Spatial features for the region may be extracted from spatially-related data for the region. The spatially-related data may include information on fixed infrastructures in the region. Likewise, temporal features for the region may be extracted from temporally-related data for the region that changes over time. A co-training based learning framework may be further applied to co-train a spatial classifier and a temporal classifier based at least on the labeled air quality index data, the spatial features for the region, and the temporal features for the region.
    • 使用多个数据源的数据可以为多个地区的特定污染物提供推测的空气质量指标,而无需向这些地区添加空气质量监测站。 可以从一个或多个空气质量监测站获得区域中污染物的标签空气质量指数数据。 该区域的空间特征可以从该区域的空间相关数据中提取。 与空间有关的数据可能包括有关该地区固定基础设施的信息。 类似地,可以从随时间变化的区域的时间相关数据中提取该区域的时间特征。 基于共同训练的学习框架可以进一步应用于至少基于标记的空气质量指数数据,该区域的空间特征和该区域的时间特征来共同训练空间分类器和时间分类器。