Invention Grant
- Patent Title: Text normalization based on a data-driven learning network
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Application No.: US15673574Application Date: 2017-08-10
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Publication No.: US10395654B2Publication Date: 2019-08-27
- Inventor: Ladan Golipour , Matthias Neeracher , Ramya Rasipuram
- Applicant: Apple Inc.
- Applicant Address: US CA Cupertino
- Assignee: Apple Inc.
- Current Assignee: Apple Inc.
- Current Assignee Address: US CA Cupertino
- Agency: Dentons US LLP
- Main IPC: G10L15/00
- IPC: G10L15/00 ; G10L15/22 ; G10L15/18 ; G10L15/16 ; G10L15/26 ; G10L15/30 ; G10L13/08

Abstract:
Systems and processes for operating an intelligent automated assistant to perform text-to-speech conversion are provided. An example method includes, at an electronic device having one or more processors, receiving a text corpus comprising unstructured natural language text. The method further includes generating a sequence of normalized text based on the received text corpus; and generating a pronunciation sequence representing the sequence of the normalized text. The method further includes causing an audio output to be provided to the user based on the pronunciation sequence. At least one of the sequence of normalized text and the pronunciation sequence is generated based on a data-driven learning network.
Public/Granted literature
- US20180330729A1 TEXT NORMALIZATION BASED ON A DATA-DRIVEN LEARNING NETWORK Public/Granted day:2018-11-15
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