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公开(公告)号：US09972311B2
公开(公告)日：2018-05-15
申请号：US14271962
申请日：2014-05-07
CPC分类号： G10L15/18 , G06F17/2715 , G06F17/278
摘要： Systems and methods are provided for optimizing language models for in-domain applications through an iterative, joint-modeling approach that expresses training material as alternative representations of higher-level tokens, such as named entities and carrier phrases. From a first language model, an in-domain training corpus may be represented as a set of alternative parses of tokens. Statistical information determined from these parsed representations may be used to produce a second (or updated) language model, which is further optimized for the domain. The second language model may be used to determine another alternative parsed representation of the corpus for a next iteration, and the statistical information determined from this representation may be used to produce a third (or further updated) language model. Through each iteration, a language model may be determined that is further optimized for the domain.
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公开(公告)号：US09672202B2
公开(公告)日：2017-06-06
申请号：US14220916
申请日：2014-03-20
CPC分类号： G06F17/276 , G06F17/273 , G10L15/24 , G10L15/26
摘要： Various components provide options to re-format an input based on one or more contexts. The input is received that has been submitted to an application (e.g., messaging application, mobile application, word-processing application, web browser, search tool, etc.), and one or more outputs are identified that are possibilities to be provided as options for re-formatting. A respective score of each output is determined by applying a statistical model to a respective combination of the input and each output, the respective score comprising a plurality of context scores that quantify a plurality of contexts of the respective combination. Exemplary contexts include historical-user contexts, domain contexts, and general contexts. One or more suggested outputs are selected from among the one or more outputs based on the respective scores and are provided as options to re-format the input.
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公开(公告)号：US20150325235A1
公开(公告)日：2015-11-12
申请号：US14271962
申请日：2014-05-07
IPC分类号： G10L15/18
CPC分类号： G10L15/18 , G06F17/2715 , G06F17/278
摘要： Systems and methods are provided for optimizing language models for in-domain applications through an iterative, joint-modeling approach that expresses training material as alternative representations of higher-level tokens, such as named entities and carrier phrases. From a first language model, an in-domain training corpus may be represented as a set of alternative parses of tokens. Statistical information determined from these parsed representations may be used to produce a second (or updated) language model, which is further optimized for the domain. The second language model may be used to determine another alternative parsed representation of the corpus for a next iteration, and the statistical information determined from this representation may be used to produce a third (or further updated) language model. Through each iteration, a language model may be determined that is further optimized for the domain.
摘要翻译： 提供了系统和方法，用于通过迭代的联合建模方法来优化域内应用程序的语言模型，该方法将培训材料表示为更高层令牌（如命名实体和运营商短语）的替代表示。 从第一语言模型，域内训练语料库可以被表示为令牌的替代解析集合。 从这些解析的表示中确定的统计信息可以用于产生第二（或更新的）语言模型，该模型针对域被进一步优化。 可以使用第二语言模型来确定用于下一次迭代的语料库的另一替代解析表示，并且可以使用从该表示确定的统计信息来产生第三（或进一步更新的）语言模型。 通过每次迭代，可以确定针对域进一步优化的语言模型。
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公开(公告)号：US20150278191A1
公开(公告)日：2015-10-01
申请号：US14227492
申请日：2014-03-27
IPC分类号： G06F17/27
CPC分类号： G10L15/183 , G06F17/2755 , G06F17/2785 , G10L15/30
摘要： The customization of language modeling components for speech recognition is provided. A list of language modeling components may be made available by a computing device. A hint may then be sent to a recognition service provider for combining the multiple language modeling components from the list. The hint may be based on a number of different domains. A customized combination of the language modeling components based on the hint may then be received from the recognition service provider.
摘要翻译： 提供了用于语音识别的语言建模组件的定制。 语言建模组件的列表可以由计算设备提供。 然后，可以向识别服务提供商发送提示，以从列表中组合多个语言建模组件。 提示可能基于许多不同的域。 然后可以从识别服务提供商接收基于提示的语言建模组件的定制组合。
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公开(公告)号：US20150243278A1
公开(公告)日：2015-08-27
申请号：US14186476
申请日：2014-02-21
CPC分类号： G10L15/187 , G10L15/01 , G10L15/075 , G10L2015/025 , G10L2015/225
摘要： A new pronunciation learning system for dynamically learning new pronunciations assisted by user correction logs. The user correction logs provide a record of speech recognition events and subsequent user behavior that implicitly confirms or rejects the recognition result and/or shows the user's intended words by via subsequent input. The system analyzes the correction logs and distills them down to a set of words which lack acceptable pronunciations. Hypothetical pronunciations, constrained by spelling and other linguistic knowledge, are generated for each of the words. Offline recognition determines the hypothetical pronunciations with a good acoustical match to the audio data likely to contain the words. The matching pronunciations are aggregated and adjudicated to select new pronunciations for the words to improve general or personalized recognition models.
摘要翻译： 一种用于动态学习由用户校正日志辅助的新发音的新发音学习系统。 用户校正日志提供语音识别事件和后续用户行为的记录，其隐含地确认或拒绝识别结果和/或通过后续输入显示用户的预期词语。 系统对校正日志进行分析，并将其解释为一组缺乏可接受发音的单词。 为每个单词生成假说发音，受到拼写和其他语言知识的约束。 离线识别确定具有与可能包含单词的音频数据良好声学匹配的假设发音。 匹配的发音被聚合和裁决，以选择新的发音来改善一般或个性化的识别模型。
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