System and method for characterizing voiced excitations of speech and acoustic signals, removing acoustic noise from speech, and synthesizing speech

• US 20040083100A1
• Filed: 10/08/2003
• Published: 04/29/2004
• Est. Priority Date: 02/06/1996
• Status: Active Grant

• Current Assignee: Lawrence Livermore National Security LLC (Government of the United States of America)
• Original Assignee: Regents of the University of California (University of California)
• Inventors: Ng, Lawrence C., Burnett, Greg C., Holzrichter, John F.
• Granted Patent: US 7,035,795 B2
• Time in Patent Office: Days
• US Class Current: 704/233
• CPC Class Codes: A61B 5/0507 using microwaves or terahertz waves
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: G01N 2291/02491 Materials with nonlinear acoustic properties
• CPC Class Codes: G01N 2291/02872 Pressure
• CPC Class Codes: G06F 18/256 of results relating to different input data, e.g. multimodal recognition
• CPC Class Codes: G06V 40/10 Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
• CPC Class Codes: G10L 13/04 Details of speech synthesis systems, e.g. synthesiser structure or memory management
• CPC Class Codes: G10L 15/24 Speech recognition using non-acoustical features

Abstract

The present invention is a system and method for characterizing human (or animate) speech voiced excitation functions and acoustic signals, for removing unwanted acoustic noise which often occurs when a speaker uses a microphone in common environments, and for synthesizing personalized or modified human (or other animate) speech upon command from a controller. A low power EM sensor is used to detect the motions of windpipe tissues in the glottal region of the human speech system before, during, and after voiced speech is produced by a user. From these tissue motion measurements, a voiced excitation function can be derived. Further, the excitation function provides speech production information to enhance noise removal from human speech and it enables accurate transfer functions of speech to be obtained. Previously stored excitation and transfer functions can be used for synthesizing personalized or modified human speech. Configurations of EM sensor and acoustic microphone systems are described to enhance noise cancellation and to enable multiple articulator measurements.

Claims

1. A method for removing acoustic noise from an acoustic speech signal, comprising the steps of:

selecting a first set of acoustic speech time frames with timing defined by an excitation function determined using an EM sensor;

characterizing qualities of an acoustic noise signal over a second set of time frames with timing defined by an excitation function determined using the EM sensor and by using the acoustic speech signal over said second set of time frames;

constructing an acoustic noise filter appropriate to the acoustic speech signal over the first set of time frames and to the characterized noise signal over the second set of time frames; and

filtering the acoustic noise signal from the acoustic speech signal over the first set of time frames using the acoustic noise filter.

2. The method of claim 1, wherein:

the characterizing step includes the step of characterizing the qualities of the acoustic noise signal over the first set of time frames; and

the constructing step includes the step of constructing the acoustic noise filter using both acoustic speech signal and noise signal information over the first set of time frames.

3. The method of claim 1 wherein the characterizing step includes the step of characterizing the qualities of the acoustic noise signal over a predetermined portion of a no-speech time period.