发明名称 |
SELF-LEARNING STATISTICAL NATURAL LANGUAGE PROCESSING FOR AUTOMATIC PRODUCTION OF VIRTUAL PERSONAL ASSISTANTS |
摘要 |
Technologies for natural language request processing include a computing device having a semantic compiler to generate a semantic model based on a corpus of sample requests. The semantic compiler may generate the semantic model by extracting contextual semantic features or processing ontologies. The computing device generates a semantic representation of a natural language request by generating a lattice of candidate alternative representations, assigning a composite weight to each candidate, and finding the best route through the lattice. The composite weight may include semantic weights, phonetic weights, and/or linguistic weights. The semantic representation identifies a user intent and slots associated with the natural language request. The computing device may perform one or more dialog interactions based on the semantic request, including generating a request for additional information or suggesting additional user intents. The computing device may support automated analysis and tuning to improve request processing. Other embodiments are described and claimed. |
申请公布号 |
US2015032443(A1) |
申请公布日期 |
2015.01.29 |
申请号 |
US201414341013 |
申请日期 |
2014.07.25 |
申请人 |
Karov Yael;Breakstone Micha;Shilon Reshef;Keller Orgad;Shellef Eric |
发明人 |
Karov Yael;Breakstone Micha;Shilon Reshef;Keller Orgad;Shellef Eric |
分类号 |
G06F17/27 |
主分类号 |
G06F17/27 |
代理机构 |
|
代理人 |
|
主权项 |
1. A computing device for interpreting natural language requests, the computing device comprising:
a semantic compiler module to generate a semantic model as a function of a corpus of predefined requests, wherein the semantic model includes a plurality of mappings between a natural language request and a semantic representation of the natural language request, wherein the semantic representation identifies a user intent and zero or more slots associated with the user intent; and a request decoder module to:
generate, using the semantic model, a lattice of candidate alternatives indicative of a natural language request, wherein each candidate alternative corresponds to a token of the natural language request;assign a composite confidence weight to each candidate alternative as a function of the semantic model;determine an optimal route through the candidate alternative lattice based on the associated confidence weight; andgenerate a semantic representation of the natural language request as a function of the candidate alternatives of the optimal route. |
地址 |
Tel Aviv IL |