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.

Date of Patent:
Sep. 27, 2016

Filed:

Mar. 13, 2013
Applicant:

Kabushiki Kaisha Toshiba, Tokyo, JP;

Inventors:

Javier Latorre-Martinez, Cambridge, GB;

Vincent Ping Leung Wan, Cambridge, GB;

Kean Kheong Chin, Cambridge, GB;

Mark John Francis Gales, Cambridge, GB;

Katherine Mary Knill, Cambridge, GB;

Masami Akamine, Cambridge, GB;

Byung Ha Chung, Cambridge, GB;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/00 (2013.01); G10L 15/26 (2006.01); G10L 13/033 (2013.01); G10L 13/08 (2013.01); G10L 21/013 (2013.01);
U.S. Cl.
CPC ...
G10L 15/26 (2013.01); G10L 13/033 (2013.01); G10L 13/08 (2013.01); G10L 2021/0135 (2013.01);
Abstract

A text-to-speech method for simulating a plurality of different voice characteristics includes dividing inputted text into a sequence of acoustic units; selecting voice characteristics for the inputted text; converting the sequence of acoustic units to a sequence of speech vectors using an acoustic model having a plurality of model parameters provided in clusters each having at least one sub-cluster and describing probability distributions which relate an acoustic unit to a speech vector; and outputting the sequence of speech vectors as audio with the selected voice characteristics. A parameter of a predetermined type of each probability distribution is expressed as a weighted sum of parameters of the same type using voice characteristic dependent weighting. In converting the sequence of acoustic units to a sequence of speech vectors, the voice characteristic dependent weights for the selected voice characteristics are retrieved for each cluster such that there is one weight per sub-cluster.


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