公开(公告)号：WO2014120699A2

公开(公告)日：2014-08-07

申请号：PCT/US2014/013469

申请日：2014-01-29

Applicant: MICROSOFT CORPORATION

Inventor： SARIKAYA, Ruhi ,  DEORAS, Anoop ,  CELIKYILMAZ, Fethiye Asli ,  JANARDHANA, Ravikiran ,  BOIES, Daniel

IPC: G06F17/27

CPC classification number: G06F17/279 ,  G06F17/30672

Abstract: A scalable statistical language understanding (SLU) system uses a fixed number of understanding models that scale across domains and intents (i.e. single vs. multiple intents per utterance). For each domain added to the SLU system, the fixed number of existing models is updated to reflect the newly added domain. Information that is already included in the existing models and the corresponding training data may be re-used. The fixed models may include a domain detector model, an intent action detector model, an intent object detector model and a slot/entity tagging model. A domain detector identifies different domains identified within an utterance. All/portion of the detected domains are used to determine associated intent actions. For each determined intent action, one or more intent objects are identified. Slot/entity tagging is performed using the determined domains, intent actions, and intent object detector.

Abstract translation: 可扩展的统计语言理解（SLU）系统使用固定数量的理解模型来扩展域和意图（即每个话语的单个对多个意图）。 对于添加到SLU系统的每个域，将更新固定数量的现有模型以反映新添加的域。 已经包含在现有模型中的信息和相应的训练数据可能被重新使用。 固定模型可以包括域检测器模型，意图动作检测器模型，意图对象检测器模型和时隙/实体标签模型。 域检测器识别在话语内识别的不同域。 检测到的域的全部/部分用于确定相关联的意图动作。 对于每个确定的意图行为，识别一个或多个意图对象。 使用确定的域，意图动作和意图对象检测器执行插槽/实体标记。