IP Library › Patent Application 15428828
Patent Application
App. No. 15/428,828

LATENT-SEGMENTATION INTONATION MODEL

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Quick Facts
Patent No.
US None
App. No.
15/428,828
Abstract

The intonation model of the present technology disclosed herein assigns different words within a sentence to be prominent, analyzes multiple prominence possibilities (in some cases, all prominence possibilities), and learns parameters of the model using large amounts of data. Unlike previous systems, intonation patterns are discovered from data. Speech data is sub-segmented into words, the different segments are analyzed and used for learning, and a determination is made as to whether the segmentations predict pitch

Claims (20)

1 . A method for performing speech synthesis, comprising:

receiving, by an application on a computing device, data for a collection of words;

marking one or more of the collection of words with prominence data by the application;

determining parameters based on the prominence data; and

generating by the application synthesized speech data based on the determined parameters.

2 . The method of claim 1 , further comprising marking, by the application on the computing device, one or more syllables of the words with prominence data.

3 . The method of claim 2 , wherein the syllables are prominent syllables.

4 . The method of claim 1 , further comprising assigning one or more of the parameters to a word of the collection of words.

5 . The method of claim 1 , wherein the computing device includes a mobile device, the application including a mobile application in communication with remote server.

6 . The method of claim 1 , wherein the computing device includes a server, the server in communication with a mobile device.

7 . A non-transitory computer readable medium for performing speech synthesis, comprising:

receiving, by an application on a computing device, data for a collection of words;

marking one or more of the collection of words with prominence data by the application;

determining parameters based on the prominence data; and

generating by the application synthesized speech data based on the determined parameters.

8 . The non-transitory computer readable medium of claim 7 , further comprising marking, by the application on the computing device, one or more syllables of the words with prominence data.

9 . The non-transitory computer readable medium of of claim 8 , wherein the syllables are prominent syllables.

10 . The non-transitory computer readable medium of claim 7 , further comprising assigning one or more of the parameters to a word of the collection of words.

11 . The non-transitory computer readable medium of claim 7 , wherein the computing device includes a mobile device, the application including a mobile application in communication with remote server.

12 . The non-transitory computer readable medium of claim 7 , wherein the computing device includes a server, the server in communication with a mobile device.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 28, 2020
From: SEMANTIC MACHINES, INC.
To: MICROSOFT TECHNOLOGY LICENSING, LLC
Reel/Frame 053904/0601 →
CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNMENT DOCUMENT TO REPLACE DIGITAL SIGNATURES PREVIOUSLY RECORDED AT REEL: 045379 FRAME: 0403. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Jan 4, 2019
From: BERG-KIRKPATRICK, TAYLOR DARWIN; CHANG, WILLIAM HUI-DEE; HALL, DAVID LEO WRIGHT; KLEIN, DANIEL
To: SEMANTIC MACHINES, INC.
Reel/Frame 049747/0516 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 28, 2018
From: BERG-KIRKPATRICK, TAYLOR DARWIN; CHANG, WILLIAM HUI-DEE; HALL, DAVID LEO WRIGHT; KLEIN, DANIEL
To: SEMANTIC MACHINES, INC.
Reel/Frame 045379/0403 →