公开(公告)号：WO2009035825A2

公开(公告)日：2009-03-19

申请号：PCT/US2008/073570

申请日：2008-08-19

Applicant: MICROSOFT CORPORATION

Inventor： LI, Xiaolong ,  DENG, Li ,  JU, Yun-cheng ,  ACERO, Alex

IPC: G09B17/00 ,  G09B5/06 ,  G10L21/00

CPC classification number: G10L15/18 ,  G09B17/003 ,  G10L15/183

Abstract: A method of providing automatic reading tutoring is disclosed. The method includes retrieving a textual indication of a story from a data store and creating a language model including constructing a target context free grammar indicative of a first portion of the story. A first acoustic input is received and a speech recognition engine is employed to recognize the first acoustic input. An output of the speech recognition engine is compared to the language model and a signal indicative of whether the output of the speech recognition matches at least a portion of the target context free grammar is provided.

Abstract translation: 公开了提供自动阅读辅导的方法。 该方法包括从数据存储中检索故事的文本指示并创建包括构建指示故事的第一部分的目标上下文自由语法的语言模型。 接收到第一声输入，并且采用语音识别引擎来识别第一声输入。 将语音识别引擎的输出与语言模型进行比较，并且提供指示语音识别的输出是否与目标语境自由语法的至少一部分匹配的信号。

公开(公告)号：WO2009120449A1

公开(公告)日：2009-10-01

申请号：PCT/US2009/035389

申请日：2009-02-27

Applicant: MICROSOFT CORPORATION

Inventor： LI, Xiao ,  JU, Yun-cheng ,  ZWEIG, Geoffrey ,  ACERO, Alex

IPC: G06F17/28 ,  G06F17/27 ,  G06F17/20

CPC classification number: G06F17/2818 ,  G06F17/2827

Abstract: Training data may be provided, the training data including pairs of source phrases and target phrases. The pairs may be used to train an intra-language statistical machine translation model, where the intra-language statistical machine translation model, when given an input phrase of text in the human language, can compute probabilities of semantic equivalence of the input phrase to possible translations of the input phrase in the human language. The statistical machine translation model may be used to translate between queries and listings. The queries may be text strings in the human language submitted to a search engine. The listing strings may be text strings of formal names of real world entities that are to be searched by the search engine to find matches for the query strings.

Abstract translation: 可以提供训练数据，训练数据包括源短语和目标短语对。 这些对可以用于训练语言间统计机器翻译模型，其中语言内统计机器翻译模型在给予人类语言的文本的输入短语时可以计算输入短语的语义等同性的可能性 输入短语在人类语言中的翻译。 统计机器翻译模型可用于在查询和列表之间进行翻译。 查询可以是提交给搜索引擎的人类语言中的文本字符串。 列表字符串可以是要由搜索引擎搜索以查找查询字符串的匹配的真实世界实体的正式名称的文本串。

公开(公告)号：WO2008089469A1

公开(公告)日：2008-07-24

申请号：PCT/US2008/051582

申请日：2008-01-21

Applicant: MICROSOFT CORPORATION

Inventor： LI, Xiaolong ,  JU, Yun-cheng ,  DENG, Li ,  ACERO, Alejandro

IPC: G06F17/28

CPC classification number: G06F17/271 ,  G09B17/003 ,  G10L15/197 ,  G10L2015/221

Abstract: A novel system for automatic reading tutoring provides effective error detection and reduced false alarms combined with low processing time burdens and response times short enough to maintain a natural, engaging flow of interaction. According to one illustrative embodiment, an automatic reading tutoring method includes displaying a text output and receiving an acoustic input. The acoustic input is modeled with a domain-specific target language model specific to the text output, and with a general-domain garbage language model, both of which may be efficiently constructed as context-free grammars. The domain-specific target language model may be built dynamically or "on-the-fly" based on the currently displayed text (eg the story to be read by the user), while the general-domain garbage language model is shared among all different text outputs. User-perceptible tutoring feedback is provided based on the target language model and the garbage language model.

Abstract translation: 用于自动阅读辅导的新颖系统提供了有效的错误检测和减少的假警报以及较短的处理时间负担和响应时间足够短以保持自然的，互动的互动流。 根据一个说明性实施例，自动阅读辅导方法包括显示文本输出并接收声输入。 声输入是用专门针对文本输出的领域特定的目标语言模型建立的，并且具有通用域垃圾语言模型，这两种语言模型都可以被有效地构建为无上下文的语法。 可以基于当前显示的文本（例如，用户要阅读的故事）动态地或“即时”地构建域特定目标语言模型，而一般域垃圾语言模型在所有不同的方式之间共享 文本输出。 基于目标语言模型和垃圾语言模型提供了用户可感知的辅导反馈。