首页> 外国专利> Determining prosodic markings for text-to-speech systems - using neural network to determine prosodic markings based on linguistic categories such as number, verb, verb particle, pronoun, preposition etc.

Determining prosodic markings for text-to-speech systems - using neural network to determine prosodic markings based on linguistic categories such as number, verb, verb particle, pronoun, preposition etc.

机译:确定文本到语音系统的韵律标记-使用神经网络基于语言类别(例如数字,动词,动词质点,代词,介词等)确定韵律标记。

摘要

The method involves using a neural network (1) to determine prosodic markings e.g. phrase boundaries based on linguistic categories. The markings are evaluated. The linguistic categories of at least three words of a text to be synthesised are applied to the input of the neural network. The characteristics of each prosodic marking are detected by neuronal auto-associators (7) which are trained respectively for a certain prosodic marking. The output information from each auto-associator is evaluated in a neural classifier.
机译:该方法涉及使用神经网络(1)来确定韵律标记,例如音调标记。基于语言类别的短语边界。对标记进行评估。将要合成的文本的至少三个单词的语言类别应用于神经网络的输入。每个韵律标记的特征由神经元自动关联器(7)检测,神经元自动关联器分别针对某个韵律标记进行训练。来自每个自动关联器的输出信息在神经分类器中进行评估。

著录项

  • 公开/公告号DE10018134A1

    专利类型

  • 公开/公告日2001-10-18

    原文格式PDF

  • 申请/专利权人 SIEMENS AG;

    申请/专利号DE2000118134

  • 申请日2000-04-12

  • 分类号G10L13/08;

  • 国家 DE

  • 入库时间 2022-08-22 01:09:51

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