ACOUSTIC MODEL LEARNING DEVICE, VOICE SYNTHESIS DEVICE, METHOD, AND PROGRAM

Title:

ACOUSTIC MODEL LEARNING DEVICE, VOICE SYNTHESIS DEVICE, METHOD, AND PROGRAM

Document Type and Number:

WIPO Patent Application WO/2021/033629

Kind Code:

A1

Abstract:

The present invention provides a voice synthesis technology based on a low-delay and properly modeled DNN in a computational resource-limited environment.　Provided is an acoustic model learning device comprising: a corpus storage unit which stores, on an utterance-by-utterance basis, natural language feature amount series and natural voice parameter series that are extracted from a plurality of utterance voices; a prediction model storage unit which stores a feedforward neural network-type prediction model for predicting some synthesized voice parameter series from some natural language feature amount series; a voice parameter series prediction unit to which the natural language feature amount series is inputted, and which predicts the synthesized voice parameter series using the prediction model; an error totalizer which totalizes errors relating to the synthesized voice parameter series and the natural voice parameter series; and a learning unit which performs predetermined optimization on the error and learns the prediction model. The error totalizer uses a loss function for associating frames adjacent to an output layer of the prediction model with each other.

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Inventors:

MATSUNAGA NORIYUKI (JP)
OHTANI YAMATO (JP)

Application Number:

PCT/JP2020/030833

Publication Date:

February 25, 2021

Filing Date:

August 14, 2020

Export Citation:

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Assignee:

AI INC (JP)

International Classes:

G10L13/047; G10L13/06; G10L25/30

Foreign References:

US8527276B1	2013-09-03
JP2017032839A	2017-02-09

Other References:

ZEN, H. G., ANDREW SENIOR, MIKE SCHUSTER: "Statistical parametric speech synthesis using deep neural networks", PROC. ICASSP 2013, May 2013 (2013-05-01), pages 7962 - 7966, XP055794938
See also references of EP 4020464A4