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    • 1. 发明授权
    • Distributed real time speech recognition system
    • 分布式实时语音识别系统
    • US09076448B2
    • 2015-07-07
    • US10684357
    • 2003-10-10
    • Ian M. BennettBandi Ramesh BabuKishor MorkhandikarPallaki Gururaj
    • Ian M. BennettBandi Ramesh BabuKishor MorkhandikarPallaki Gururaj
    • G10L15/02G10L15/22G10L17/22G06F17/30G10L15/00G10L15/183G10L15/30G06F17/28G10L15/18G10L15/14
    • G10L17/22G06F17/289G06F17/3043G10L15/005G10L15/142G10L15/18G10L15/183G10L15/22G10L15/30Y10S707/99935
    • A real-time system incorporating speech recognition and linguistic processing for recognizing a spoken query by a user and distributed between client and server, is disclosed. The system accepts user's queries in the form of speech at the client where minimal processing extracts a sufficient number of acoustic speech vectors representing the utterance. These vectors are sent via a communications channel to the server where additional acoustic vectors are derived. Using Hidden Markov Models (HMMs), and appropriate grammars and dictionaries conditioned by the selections made by the user, the speech representing the user's query is fully decoded into text (or some other suitable form) at the server. This text corresponding to the user's query is then simultaneously sent to a natural language engine and a database processor where optimized SQL statements are constructed for a full-text search from a database for a recordset of several stored questions that best matches the user's query. Further processing in the natural language engine narrows the search to a single stored question. The answer corresponding to this single stored question is next retrieved from the file path and sent to the client in compressed form. At the client, the answer to the user's query is articulated to the user using a text-to-speech engine in his or her native natural language. The system requires no training and can operate in several natural languages.
    • 公开了一种包含语音识别和语言处理的实时系统,用于识别由用户进行的口语查询并分发在客户端与服务器之间。 该系统以客户端的语音形式接受用户的查询,其中最小处理提取足够数量的表示话语的声学语音向量。 这些向量经由通信信道被发送到服务器,其中导出附加的声向量。 使用隐马尔可夫模型(HMM),以及由用户做出的选择所限制的适当的语法和词典,表示用户查询的语音在服务器处被完全解码为文本(或其他合适的形式)。 然后将与用户查询相对应的文本同时发送到自然语言引擎和数据库处理器,其中为数据库构建优化的SQL语句,用于针对与用户查询最匹配的多个存储问题的记录集的全文搜索。 自然语言引擎中的进一步处理将搜索缩小到单个存储的问题。 对应于该单个存储问题的答案接下来从文件路径中检索并以压缩形式发送给客户端。 在客户端,使用他或她的母语自然语言的文本到语音引擎向用户阐述用户查询的答案。 该系统不需要培训,可以使用多种自然语言进行操作。
    • 7. 发明授权
    • Interactive speech based learning/training system formulating search queries based on natural language parsing of recognized user queries
    • US06665640B1
    • 2003-12-16
    • US09439173
    • 1999-11-12
    • Ian M. BennettBandi Ramesh BabuKishor MorkhandikarPallaki Gururaj
    • Ian M. BennettBandi Ramesh BabuKishor MorkhandikarPallaki Gururaj
    • G10L1518
    • G06F17/3043G09B5/04G09B7/00G10L15/22Y10S707/99934
    • A real-time speech-based learning/training system distributed between client and server, and incorporating speech recognition and linguistic processing for recognizing a spoken question and to provide an answer to the student in a learning or training environment implemented on an intranet or over the Internet, is disclosed. The system accepts the student's question in the form of speech at his or her computer, PDA or workstation where minimal processing extracts a sufficient number of acoustic speech vectors representing the utterance. The system as implemented accepts environmental variables such as course, chapter, section as selected by the user so that the search time, accuracy and response time for the question can be optimized. A minimum set of acoustic vectors extracted at the client are then sent via a communications channel to the server where additional acoustic vectors are derived. Using Hidden Markov Models (HMMs), and appropriate grammars and dictionaries conditioned by the course, chapter and section selections made by the student, the speech representing the user's query is fully decoding to text at the server. This text corresponding to the user's query is then simultaneously sent to a natural language engine and a database processor where an optimized SQL statement is constructed for a full-text search from a SQL database for a recordset of several stored questions that best matches the user's query. Further processing in the natural language engine narrows the search down to a single stored question. The answer that is paired to this single stored question is then retrieved from the file path and sent to the student computer in compressed form. At the student's computer, the answer is articulated using a text-to-speech engine in his or her native natural language. The system requires no training and can operate in several natural languages.
    • 8. 发明授权
    • Distributed realtime speech recognition system
    • 分布式实时语音识别系统
    • US06633846B1
    • 2003-10-14
    • US09439145
    • 1999-11-12
    • Ian M. BennettBandi Ramesh BabuKishor MorkhandikarPallaki Gururaj
    • Ian M. BennettBandi Ramesh BabuKishor MorkhandikarPallaki Gururaj
    • G10L1502
    • G06F17/3043G10L15/142G10L15/1815G10L15/183G10L15/285G10L15/30H04M2250/74
    • A real-time system incorporating speech recognition and linguistic processing for recognizing a spoken query by a user and distributed between client and server, is disclosed. The system accepts user's queries in the form of speech at the client where minimal processing extracts a sufficient number of acoustic speech vectors representing the utterance. These vectors are sent via a communications channel to the server where additional acoustic vectors are derived. Using Hidden Markov Models (HMMs), and appropriate grammars and dictionaries conditioned by the selections made by the user, the speech representing the user's query is fully decoded into text (or some other suitable form) at the server. This text corresponding to the user's query is then simultaneously sent to a natural language engine and a database processor where optimized SQL statements are constructed for a full-text search from a database for a recordset of several stored questions that best matches the user's query. Further processing in the natural language engine narrows the search to a single stored question. The answer corresponding to this single stored question is next retrieved from the file path and sent to the client in compressed form. At the client, the answer to the user's query is articulated to the user using a text-to-speech engine in his or her native natural language. The system requires no training and can operate in several natural languages.
    • 公开了一种包含语音识别和语言处理的实时系统,用于识别由用户进行的口语查询并分发在客户端与服务器之间。 该系统以客户端的语音形式接受用户的查询,其中最小处理提取足够数量的表示话语的声学语音向量。 这些向量经由通信信道被发送到服务器,其中导出附加的声向量。 使用隐马尔可夫模型(HMM),以及由用户做出的选择所限制的适当的语法和词典,表示用户查询的语音在服务器处被完全解码为文本(或其他合适的形式)。 然后将与用户查询相对应的文本同时发送到自然语言引擎和数据库处理器,其中为数据库构建优化的SQL语句,用于针对与用户查询最匹配的多个存储问题的记录集的全文搜索。 自然语言引擎中的进一步处理将搜索缩小到单个存储的问题。 对应于该单个存储问题的答案接下来从文件路径检索并以压缩形式发送给客户端。 在客户端,使用他或她的母语自然语言的文本到语音引擎向用户阐述用户查询的答案。 该系统不需要训练,可以使用多种自然语言进行操作。