The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jan. 07, 2025
Filed:
Nov. 21, 2023
Google Llc, Mountain View, CA (US);
Samuel Bengio, Los Altos, CA (US);
Yuxuan Wang, Sunnyvale, CA (US);
Zongheng Yang, Berkeley, CA (US);
Zhifeng Chen, Sunnyvale, CA (US);
Yonghui Wu, Fremont, CA (US);
Ioannis Agiomyrgiannakis, London, GB;
Ron J. Weiss, New York, NY (US);
Navdeep Jaitly, Mountain View, CA (US);
Ryan M. Rifkin, Oakland, CA (US);
Robert Andrew James Clark, Hertfordshire, GB;
Quoc V. Le, Sunnyvale, CA (US);
Russell J. Ryan, Mountain View, CA (US);
Ying Xiao, San Bruno, CA (US);
Google LLC, Mountain View, CA (US);
Abstract
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating speech from text. One of the systems includes one or more computers and one or more storage devices storing instructions that when executed by one or more computers cause the one or more computers to implement: a sequence-to-sequence recurrent neural network configured to: receive a sequence of characters in a particular natural language, and process the sequence of characters to generate a spectrogram of a verbal utterance of the sequence of characters in the particular natural language; and a subsystem configured to: receive the sequence of characters in the particular natural language, and provide the sequence of characters as input to the sequence-to-sequence recurrent neural network to obtain as output the spectrogram of the verbal utterance of the sequence of characters in the particular natural language.