公开(公告)号：US20160358598A1

公开(公告)日：2016-12-08

申请号：US14846667

申请日：2015-09-04

Applicant: Apple Inc.

Inventor： Shaun E. WILLIAMS ,  Henry G. MASON ,  Mahesh KRISHNAMOORTHY ,  Matthias PAULIK ,  Neha AGRAWAL ,  Sachin S. KAJAREKAR ,  Selen UGUROGLU ,  Ali S. MOHAMED

IPC: G10L15/04 ,  G10L17/02 ,  G10L25/87

CPC classification number: G10L15/04 ,  G10L17/02 ,  G10L25/87 ,  G10L2025/783

Abstract: The present disclosure generally relates to context-based endpoint detection in user speech input. A method for identifying an endpoint of a spoken request by a user may include receiving user input of natural language speech including one or more words; identifying at least one context associated with the user input; generating a probability, based on the at least one context associated with the user input, that a location in the user input is an endpoint; determining whether the probability is greater than a threshold; and in accordance with a determination that the probability is greater than the threshold, identifying the location in the user input as the endpoint.

Abstract translation: 本公开通常涉及用户语音输入中的基于上下文的端点检测。 用于识别用户的口头请求的端点的方法可以包括接收包括一个或多个单词的自然语言语言的用户输入; 识别与所述用户输入相关联的至少一个上下文; 基于与所述用户输入相关联的所述至少一个上下文，生成所述用户输入中的位置是端点的概率; 确定概率是否大于阈值; 并且根据概率大于阈值的确定，将用户输入中的位置识别为端点。

公开(公告)号：US20160093298A1

公开(公告)日：2016-03-31

申请号：US14835520

申请日：2015-08-25

Applicant: Apple Inc.

Inventor： Devang K. NAIK ,  Ali S. MOHAMED ,  Hong M. CHEN

IPC: G10L15/183 ,  G10L15/00 ,  G10L15/26 ,  G10L13/08

CPC classification number: G10L15/183 ,  G10L13/08 ,  G10L15/005 ,  G10L15/063 ,  G10L15/187 ,  G10L15/26 ,  G10L2015/228

Abstract: Systems and processes for generating a shared pronunciation lexicon and using the shared pronunciation lexicon to interpret spoken user inputs received by a virtual assistant are provided. In one example, the process can include receiving pronunciations for words or named entities from multiple users. The pronunciations can be tagged with context tags and stored in the shared pronunciation lexicon. The shared pronunciation lexicon can then be used to interpret a spoken user input received by a user device by determining a relevant subset of the shared pronunciation lexicon based on contextual information associated with the user device and performing speech-to-text conversion on the spoken user input using the determined subset of the shared pronunciation lexicon.

Abstract translation: 提供了用于生成共享发音词典和使用共享发音词典来解释由虚拟助理接收的口语用户输入的系统和过程。 在一个示例中，该过程可以包括从多个用户接收单词或命名实体的发音。 发音可以用上下文标签标记，并存储在共享的发音词典中。 然后，共享的发音词典可以用于通过基于与用户设备相关联的上下文信息并且在口语用户上执行语音到文本转换来确定共享发音词典的相关子集来解释由用户设备接收的口语用户输入 输入使用确定的共享发音词典的子集。