公开(公告)号：US09460711B1

公开(公告)日：2016-10-04

申请号：US13862541

申请日：2013-04-15

Applicant: Google Inc.

Inventor： Vincent Olivier Vanhoucke ,  Jeffrey Adgate Dean ,  Georg Heigold ,  Marc'aurelio Ranzato ,  Matthieu Devin ,  Patrick An Phu Nguyen ,  Andrew William Senior

IPC: G10L15/00 ,  G10L15/16 ,  G06F17/28 ,  G10L15/26

CPC classification number: G10L15/16 ,  G10L15/063 ,  G10L15/144

Abstract: Methods and systems for processing multilingual DNN acoustic models are described. An example method may include receiving training data that includes a respective training data set for each of two or more or languages. A multilingual deep neural network (DNN) acoustic model may be processed based on the training data. The multilingual DNN acoustic model may include a feedforward neural network having multiple layers of one or more nodes. Each node of a given layer may connect with a respective weight to each node of a subsequent layer, and the multiple layers of one or more nodes may include one or more shared hidden layers of nodes and a language-specific output layer of nodes corresponding to each of the two or more languages. Additionally, weights associated with the multiple layers of one or more nodes of the processed multilingual DNN acoustic model may be stored in a database.

Abstract translation: 描述了处理多语言DNN声学模型的方法和系统。 示例性方法可以包括接收包括用于两种或多种或多种语言中的每一种的相应训练数据集的训练数据。 可以基于训练数据处理多语言深层神经网络（DNN）声学模型。 多语言DNN声学模型可以包括具有一个或多个节点的多个层的前馈神经网络。 给定层的每个节点可以将相应权重连接到后续层的每个节点，并且一个或多个节点的多个层可以包括节点的一个或多个共享隐藏层和对应于节点的语言特定输出层 每种两种或多种语言。 另外，与经处理的多语言DNN声学模型的一个或多个节点的多个层相关联的权重可以存储在数据库中。