HEARING ATTENTIONAL STATE ESTIMATION APPARATUS, LEARNING APPARATUS, METHOD, AND PROGRAM THEREOF

1 . An auditory attention state estimation apparatus comprising:

a feature quantity extraction processing circuitry configured to obtain a feature quantity based on the strength of a correlation between each of a plurality of different visual stimulus patterns emitted from positions of a plurality of different sound sources and a pupil diameter change amount of a user; and

an estimation processing circuitry configured to estimate a destination to which the user pays auditory attention for a sound from the sound source using the feature quantity.

2 . The auditory attention state estimation apparatus according to claim 1 ,

wherein each of the plurality of visual stimulus patterns is a pattern of a periodically time-varying visual stimulus,

the feature quantity indicates at least a magnitude of a frequency domain pupil diameter change amount signal at a peak frequency of each of a plurality of frequency domain visual stimulus signals and/or near the peak frequency,

each of the plurality of frequency domain visual stimulus signals is a signal obtained by transforming a time-series signal indicating each of the plurality of visual stimulus patterns into a frequency domain, and

the frequency domain pupil diameter change amount signal is a signal obtained by transforming a time-series signal indicating the pupil diameter change amount into the frequency domain.

3 . The auditory attention state estimation apparatus according to claim 1 ,

wherein each of the plurality of visual stimulus patterns is a pattern of a time-varying visual stimulus, and

the feature quantity indicates at least each maximum value of a cross-correlation function between a sequence corresponding to a time-series signal indicating each of the plurality of visual stimulus patterns and a sequence corresponding to a time-series signal indicating the pupil diameter change amount.

4 . The auditory attention state estimation apparatus according to claim 1 ,

wherein the sound source corresponding to the visual stimulus pattern having a stronger correlation with the pupil diameter change amount of the user among the plurality of sound sources has a higher frequency at which the estimation processing circuitry estimates that the sound source is the destination to which the user pays auditory attention.

5 . The auditory attention state estimation apparatus according to claim 1 ,

wherein the plurality of sound sources include a first sound source,

the plurality of visual stimulus patterns includes a first visual stimulus pattern corresponding to the first sound source, and

when the strength of the correlation between the first visual stimulus pattern and the pupil diameter change amount of the user is equal to or greater than a predetermined value, the estimation processing circuitry estimates that the destination to which the user pays auditory attention is the first sound source or the vicinity of the first sound source.

6 . The auditory attention state estimation apparatus according to claim 1 ,

wherein the plurality of sound sources include a first sound source and a second sound source other than the first sound source,

the plurality of visual stimulus patterns include a first visual stimulus pattern corresponding to the first sound source and a second visual stimulus pattern corresponding to the second sound source, and

when the strength of a correlation between the first visual stimulus pattern and the pupil diameter change amount of the user is higher than the strength of a correlation between the second visual stimulus pattern and the pupil diameter change amount of the user, the estimation processing circuitry estimates that the destination to which the user pays auditory attention is the first sound source or the vicinity of the first sound source.

7 . A learning apparatus comprising:

a learning processing circuitry configured to obtain an estimation model for receiving a feature quantity based on the strength of a correlation between each of a plurality of different visual stimulus patterns emitted from positions of a plurality of different sound sources and a pupil diameter change amount of a user, and estimating a destination to which the user pays auditory attention for a sound from the sound source, through learning processing using training data in which a training feature quantity based on the strength of a correlation between each of a plurality of different training visual stimulus patterns emitted from positions of a plurality of different training sound sources and a training pupil diameter change amount is associated with correct answer information indicating a destination to which auditory attention is paid for a training sound from the training sound source.

8 . (canceled)

9 . A non-transitory computer-readable recording medium storing a program for causing a computer to function as the auditory attention state estimation apparatus according to claim 1 .

10 . A non-transitory computer-readable recording medium storing a program for causing a computer to function as the learning apparatus according to claim 7 .

11 . An auditory attention state estimation method comprising:

a feature quantity extraction step of obtaining a feature quantity based on the strength of a correlation between each of a plurality of different visual stimulus patterns emitted from positions of a plurality of different sound sources and a pupil diameter change amount of a user; and

an estimation step of estimating a destination to which the user pays auditory attention for a sound from the sound source using the feature quantity.

12 . A learning method comprising:

a learning step of obtaining an estimation model for receiving a feature quantity based on the strength of a correlation between each of a plurality of different visual stimulus patterns emitted from positions of a plurality of different sound sources and a pupil diameter change amount of a user, and estimating a destination to which the user pays auditory attention for a sound from the sound source, through learning processing using training data in which a training feature quantity based on the strength of a correlation between each of a plurality of different training visual stimulus patterns emitted from positions of a plurality of different training sound sources and a training pupil diameter change amount is associated with correct answer information indicating a destination to which auditory attention is paid for a training sound from the training sound source.