# US 12,300,210 B2 · Signal processing apparatus, signal processing method, signal processing model production method, and sound output device

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- Number: US 12,300,210 B2
- Document ID: US12300210B2
- Status: Granted
- Kind: B2
- Application number: 18/000,690
- Filed: 2021-05-26
- Published: 2023-07-13
- Granted: 2025-05-13
- Earliest claimed: 2020-06-11
- Assignees: Sony Group Corporation
- Applicants: Sony Group Corporation
- Inventors: Yasunobu Murata; Kohei Asada
- Web page: https://patentgrep.com/patent/US12300210B2

## CPC

- G10K 11/17823: {Reference signals, e.g. ambient acoustic environment}
- G10K 11/17815: {between the reference signals and the error signals, i.e. primary path}
- G10K 11/17825: {Error signals}
- G10K 11/17881: {the reference signal being an acoustic signal, e.g. recorded with a microphone}
- H04R 1/1008: {Earpieces of the supra-aural or circum-aural type}
- H04R 1/1083: {Reduction of ambient noise (active noise reduction per se G10K11/175; protective devices for the ear, e.g. providing acoustic protection A61F11/06)}
- G10K 2210/1081: Earphones, e.g. for telephones, ear protectors or headsets
- G10K 2210/3011: Single acoustic input
- G10K 2210/3024: Expert systems, e.g. artificial intelligence
- G10K 2210/3026: Feedback
- G10K 2210/3027: Feedforward
- G10K 2210/3028: Filtering, e.g. Kalman filters or special analogue or digital filters
- G10K 2210/30351: Identification of the environment for applying appropriate model characteristics
- G10K 2210/3038: Neural networks
- G10K 2210/3044: Phase shift, e.g. complex envelope processing
- G10K 2210/3048: Pretraining, e.g. to identify transfer functions
- H04R 2410/05: Noise reduction with a separate noise microphone
- H04R 2460/01: Hearing devices using active noise cancellation
- G10K: SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
- H04R: LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; ELECTRIC HEARING AIDS; PUBLIC ADDRESS SYSTEMS (producing sounds with frequency not determined by supply frequency G10K)

## Abstract

Provided is a signal processing apparatus including an acquisition unit that acquires an acoustic characteristic in a user's ear, isolated from the outside world and an NC filter unit that generates sound data having a phase opposite to an ambient sound leaking into the user's ear. The signal processing apparatus further includes a correction unit that corrects the sound data by using a correction filter and a determination unit that determines a filter coefficient of the correction filter based on the acoustic characteristic.

## Claims

### Claim 1

A signal processing apparatus, including:
an acquisition unit configured to acquire a first acoustic characteristic in a user's ear, isolated from an outside world;
an NC filter unit configured to generate sound data having a phase opposite to an ambient sound that leaks into the user's ear;
a correction unit configured to correct the sound data based on a correction filter; and
a determination unit configured to determine a filter coefficient of the correction filter, based on a trained model in which the first acoustic characteristic, a second acoustic characteristic measured in advance, and the sound data are input, and a noise suppression ratio is output.

### Claim 2 (depends on 1)

The signal processing apparatus according to claim 1, wherein
the acquisition unit is further configured to acquire the first acoustic characteristic based on a collected sound signal, and
the collected sound signal is obtained based on collection of measurement sound output into the user's ear.

### Claim 3 (depends on 1)

The signal processing apparatus according to claim 1, wherein the determination unit is further configured to determine the filter coefficient, based on the trained model that has learned, as training data, a third acoustic characteristic at a user's eardrum position.

### Claim 4 (depends on 1)

The signal processing apparatus according to claim 1, wherein the determination unit is further configured to determine the filter coefficient, based on the trained model in which whether to correct the sound data is output.

### Claim 5 (depends on 4)

The signal processing apparatus according to claim 4, wherein
the determination unit is further configured to determine the filter coefficient, based on the trained model that has learned, as training data, given information labeled to indicate whether to perform the correction by the noise suppression ratio, and
the noise suppression ratio is estimated based on the first acoustic characteristic and the sound data.

### Claim 6 (depends on 1)

The signal processing apparatus according to claim 1, wherein
the determination unit is further configured to determine the filter coefficient, based on the trained model that has learned, as training data, the noise suppression ratio, and
the noise suppression ratio is obtained based on both of a third acoustic characteristic at a user's eardrum position and the sound data.

### Claim 7 (depends on 1)

The signal processing apparatus according to claim 1, wherein
the determination unit is further configured to determine the filter coefficient, based on the trained model in which
a collected sound signal collected by a first microphone different from a second microphone having measured the first acoustic characteristic is input, and
a correction filter coefficient, that corrects a difference in the filter coefficient, based on the ambient sound in a user environment is output.

### Claim 8 (depends on 7)

The signal processing apparatus according to claim 7, wherein
the determination unit is further configured to determine the filter coefficient, based on the trained model that has learned, as training data, the correction filter coefficient, and
the correction filter coefficient corrects the difference in the filter coefficient based on a third acoustic characteristic at a user's eardrum position.

### Claim 9 (depends on 1)

The signal processing apparatus according to claim 1, wherein the determination unit is further configured to determine the filter coefficient based on the trained model in which an amount of noise canceling (NC) effect is output.

### Claim 10 (depends on 9)

The signal processing apparatus according to claim 9, wherein
the determination unit is further configured to determine the filter coefficient, based on the trained model that has learned, as training data, the amount of NC effect, and
the amount of NC effect is based on a third acoustic characteristic at a user's eardrum position.

### Claim 11 (depends on 1)

The signal processing apparatus according to claim 1, wherein
the determination unit is further configured to determine the filter coefficient, based on the trained model in which
a first amount of noise canceling (NC) effect in an environment set according to a specific standard, the sound data, and a third acoustic characteristic of ambient sound in a user environment are input, and
a second amount of NC effect in the user environment is output.

### Claim 12 (depends on 11)

The signal processing apparatus according to claim 11, wherein
the determination unit is further configured to determine the filter coefficient, based on the trained model that has learned, as training data, the second amount of NC effect, and
the second amount of NC effect is based on the sound data and the third acoustic characteristic of the ambient sound in the user environment.

### Claim 13

A signal processing method, including:
acquiring a first acoustic characteristic in a user's ear, isolated from an outside world;
generating sound data having a phase opposite to an ambient sound leaking into the user's ear;
correcting the sound data based on a correction filter; and
determining a filter coefficient of the correction filter, based on a trained model in which
the first acoustic characteristic, a second acoustic characteristic measured in advance, and the sound data are input, and
a noise suppression ratio is output.

### Claim 14

A non-transitory computer-readable medium having stored thereon computer-executable instructions that, when executed by a computer, cause the computer to execute operations, the operations comprising:
acquiring a first acoustic characteristic in a user's ear, isolated from an outside world;
generating sound data having a phase opposite to an ambient sound leaking into the user's ear;
correcting the sound data based on a correction filter; and
determining a filter coefficient of the correction filter, based on a trained model in which
the first acoustic characteristic, a second acoustic characteristic measured in advance, and the sound data are input, and
a noise suppression ratio is output.