Method for evaluating sound and system for carrying out the same

• US 6,675,114 B2
• Filed: 07/10/2002
• Issued: 01/06/2004
• Est. Priority Date: 08/15/2000
• Status: Active Grant

• Current Assignee: Yoshimasa Electronic Inc.
• Original Assignee: KOBE University
• Inventors: Sakai, Hiroyuki, Ando, Yoichi
• Primary Examiner(s): Assouad, Patrick
• Application Number:
  US10/110,307
• Publication Number:
  US 20020183947A1
• Time in Patent Office: 545 Days
• Field of Search: 702/75, 702/76, 702/77, 702/189, 702/190, 702/191, 704/200.1, 704/216, 381/71.1, 381/71.11, 381/71.12, 381/71.14
• US Class Current: 702/75
• CPC Class Codes: G01H 3/04 Frequency
• CPC Class Codes: G01H 3/10 Amplitude; Power

Abstract

A system and method (and storage media) for identifying the category of the source noise and sound by using the physical factors derived from the autocorrelation function (ACF) and the interaural crosscorrelation function (IACF) which are ever changing in the time domain based on the model of human auditory brain function system. A method for evaluating a sound comprises the steps of: using the sound recorder to capture and record the acoustic signal; calculating the ACF from the acoustic signal using a CPU; calculating ACF factors extracted from the calculated ACF using the CPU; and identifying the kinds of the noise based on the ACF factors. Thereby the unknown noise source can be identified what it is (such as automobile noise, and factory noise), and can be identified its type such as type of cars or type of machines.

Claims

1. A method for evaluating a sound, comprising the steps of:

capturing the sound and converting the captured sound into an acoustic signal;

calculating an autocorrelation function ACF from the acoustic signal with the aid of computing means;

calculating autocorrelation function factors from the calculated autocorrelation function ACF with aid of the computing means; and

evaluating the sound based on the ACF factors and a preestablished database with the aid of the computing means, said database storing at least one of the following data;

tone data associating tones with ACF factors, prosodic data associating prosodic elements with ACF factors and subjective evaluation data associating subjective evaluation values with ACF factors.

2. The method according to claim 1, wherein

said ACF factor calculating step comprises

calculating at least one of following ACF factors: energy Φ

(0) represented at the origin of delay represented by a delay time of zero;

effective duration τ

_c;

delay time of a maximum peak τ

₁;

an amplitude of a maximum peak of a normalized ACF φ

₁; and

information of respective peaks within the delay time (from zero to τ

₁)τ

_n′

, φ

_n′

(n=1, 2, 3, . . . , N (N is an integer less than approximately

     10)).

3. The method according to claim 2, wherein the method further comprises the steps of:

calculating a pitch frequency from the delay time of the maximum peak τ

₁ of the ACF; and

performing a timing by comparing the calculated pitch frequency with data of a predetermined tonal scale stored in the database to derive a difference therebetween.

4. The method according to claim 1, wherein the method further comprises the steps of:

capturing the sound in a binaural manner and converting the captured sound into acoustic binaural signals;

calculating an interaural crosscorrelation function IACF between the acoustic signals at left and right ears from the acoustic binaural signals with the aid of the computing means;

calculating interaural crosscorrelation function factors from the calculated interaural crosscorrelation function IACF with the aid of the computing means; and

evaluating the sound or evaluating subjectively the sound based on the IACF factors and/or the ACF factors and the said preestablished database with the aid the computing means.

5. The method according to claim 2, wherein the method further comprises the steps of:

capturing the sound in a binaural manner and converting the captured sound into acoustic binaural signals;

calculating an interaural crosscorrelation function IACF between the acoustic signals at left and right ears from the acoustic binaural signals with the aid of the computing means;

calculating interaural crosscorrelation function factors from the calculated interaural crosscorrelation function IACF with the aid of the computing means; and

evaluating the sound or evaluating subjectively the sound based on the IACF factors and/or the ACF factors and the said preestablished database with the aid the computing means.

6. A system for evaluating a sound comprising:

sound capturing means for capturing the sound and converting the captured sound into an acoustic signal;

ACF calculating means for calculating an autocorrelation function ACF from the acoustic sign;

ACF factor calculating means for calculating autocorrelation function factors from the calculated autocorrelation function ACF; and

evaluating means for evaluating the sound based on the ACF factors and a preestablished database, said database storing at least one of the following data;

tone data associating tones with ACF factors, prosodic data associating prosodic elements with ACF factors and subjective evaluation data associating subjective evaluation values with ACF facts.

7. The system according to claim 6, wherein

said ACE factor calculating means comprises

calculating means for calculating at least one of the following ACF factors: energy Φ

(0) represented at the origin of delay defined by a delay time of zero;

an effective duration τ

_e;

a delay time of a maximum peak τ

₁;

an amplitude of maximum peak of the normalized ACF φ

₁; and

information of respective peaks within the delay time (from zero to τ

₁)τ

_n′

, φ

_n′

(n−

1, 2, 3, . . . , N (N is an integer less than approximately

     10)).

8. The system according to claim 7, wherein

the system further comprises:

calculating means for calculating a pitch frequency from the delay time τ

₁ of the ACF; and

tuning means for comparing the calculated pitch frequency with data of a predetermined tonal scale database to represent a difference between them.

9. The system according to claim 6, further comprising:

capturing means for capturing the sound in a binaural manner and converting the captured sound into acoustic binaural signals;

IACF calculating means for calculating an interaural crosscorrelation function IACF between the acoustic signals at left and right ears from the acoustic binaural signals;

IACF factor calculating means for calculating interaural crosscorrelation function factors from the calculated interaural crosscorrelation function IACF and

evaluating means for evaluating the sound or evaluating subjectively the sound based on the IACF factors and/or the ACF factors and the said predetermined database.

10. The system according to claim 7, wherein the system further comprises:

capturing means for capturing the sound in a binaural manner and converting the captured sound into acoustic binaural signals;

IACF calculating means for calculating an interaural crosscorrelation function IACF between the acoustic signals at left and right ears from the acoustic binaural signal;

IACF factor calculating mans for calculating interaural crosscorrelation function factors from the calculated interaural crosscorrelation function IACF; and

evaluating means for evaluating the sound or evaluating subjectively the sound based on the IACF factors and/or the ACF factors and the said predetermined database.