CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a U.S. national stage entry under 35 U.S.C. 371(c) of International Application No. PCT/KR2017/015020, filed on Dec. 19, 2017, in the Korean Patent Office, which claims priority from Korean Patent Application No. 10-2016-0182792, filed on Dec. 29, 2016, in the Korean Intellectual Property Office, the disclosures of which are herein incorporated by reference in their entireties.

BACKGROUND

1. Field

Methods and apparatuses consistent with example embodiments relate to a method and an apparatus for recognizing a speaker by using a resonator.

2. Description of the Related Art

Spectrum analyzers that analyze the spectrum of sound or vibration may be used in a variety of devices. For example, spectrum analyzers may be employed in a computer, an automobile, a mobile phone, or a home appliance for speech recognition, speaker recognition, and situation recognition related to sound or vibration. Also, spectrum analyzers may be mounted on buildings, various home appliances, etc., for analyzing vibration information.

Spectrum analyzers may include sensors such as a mechanical resonator and an electrical analog or digital filter may be used to filter a signal of a frequency band of a specific region. A Fourier transform or the like may be performed by using signals obtained from the sensor to analyze the spectrum.

SUMMARY

One or more example embodiments provide a method of recognizing a speaker by using a resonator with improved accuracy and efficiency.

One or more example embodiments provide an apparatus for recognizing a speaker including a resonator with improved accuracy and efficiency.

According to an aspect of an example embodiment, provided is a method of recognizing a speaker, the method including: receiving a plurality of electrical signals corresponding to a speech of the speaker from a plurality of resonators having different resonance bands; obtaining a difference of magnitudes of the plurality of electrical signals; and recognizing the speaker based on the difference of magnitudes of the plurality of electrical signals.

The difference of magnitudes of the plurality of electrical signals may include a difference of magnitudes of electrical signals output from two resonators having neighboring resonance frequencies.

The recognizing the speaker may include generating a bitmap of a band gradient by encoding the difference of magnitudes of the plurality of electrical signals; and recognizing the speaker based on the bitmap of the band gradient.

The encoding may include converting the difference of magnitudes of the plurality of electrical signals into any one of three or more odd-number of values, by using one or more threshold values.

The three or more odd-number of values may include values that have a same absolute value and opposite signs.

The three or more odd-number of values may include −a, 0, and a (where a is a constant).

The recognizing the speaker may include registering the speaker, the registering including: generating a speaker model based on the bitmap of the band gradient; and registering the speaker model as an authentication template.

The recognizing the speaker may include determining whether the speaker is a registered speaker by performing: generating a characteristic value based on the bitmap of the band gradient; and determining whether the speaker is the registered speaker based on comparison between the characteristic value and the authentication template.

The recognizing the speaker may include determining a vowel included in the speech of the speaker based on the difference of magnitudes of the plurality of electrical signals.

The determining the vowel may include estimating relative positions of formants based on the difference of magnitudes of the plurality of electrical signals; and determining the vowel based on the relative positions of the formants.

A number of the formants may be three.

The difference of magnitudes of the plurality of electrical signals may be determined based on magnitudes of electrical signals received from four resonators of a resonator sensor.

The difference of magnitudes of the plurality of electrical signals may include a plurality of differences of magnitudes of the plurality of electrical signals, and the recognizing the speaker may include: assigning a weight to a model corresponding to the determined vowel in an authentication template; generating a bitmap of a band gradient based on a first difference of magnitudes of the plurality of electrical signals, which is different from a second difference of magnitudes of the plurality of electrical signals used to determine the vowel; generating a characteristic value based on the bitmap of the band gradient; and recognizing whether the speaker is a registered speaker based on comparison between the characteristic value and the authentication template, in which the model corresponding to the determined vowel is assigned the weight.

The assigning the weight may include: assigning the weight to the model corresponding to the determined vowel that is higher than a weight assigned to a model corresponding to another vowel.

The weight assigned to the model corresponding to the determined vowel may be 1 and the weight assigned to the model corresponding to the another vowel may be 0.

A number of the first difference of magnitudes of the plurality of electrical signals used to generate the bitmap of the band gradient may be greater than a number of the second difference of magnitudes of the plurality of electrical signals used to determine the vowel.

According to another aspect of an example embodiment, there is provided an apparatus for recognizing a speaker, the apparatus including: a resonator sensor including a plurality of resonators having different resonance bands, the plurality of resonators configured to output a plurality of electrical signals corresponding to a speech of the speaker; and a processor configured to obtain a difference of magnitudes of the plurality of electrical signals and recognize the speaker based on the difference of magnitudes of the plurality of electrical signals.

The difference of magnitudes of the plurality of electrical signals may include a difference of magnitudes of electrical signals output from two resonators having neighboring resonance frequencies.

The processor may be further configured to generate a bitmap of a band gradient by encoding the difference of magnitudes of the plurality of electrical signals and recognize the speaker based on the bitmap of the band gradient.

The processor may be further configured to encode the difference of magnitudes of the plurality of electrical signals by converting the difference of magnitudes of the plurality of electrical signals into any one of three or more odd-number of values, by using one or more threshold values.

The processor may be further configured to determine whether the speaker is a registered speaker based on comparison between a characteristic value determined based on the bitmap of the band gradient and a registered authentication template.

The processor may be further configured to determine a vowel included in the speech of the speaker based on the difference of magnitudes of the plurality of electrical signals.

The processor may be further configured to estimate relative positions of formants based on the difference of magnitudes of the plurality of electrical signals and determine the vowel based on the relative positions of the formants.

The difference of magnitudes of the plurality of electrical signals may be determined based on magnitudes of electrical signals received from four resonators of the resonator sensor.

The difference of magnitudes of the plurality of electrical signals may include a plurality of differences of magnitudes of the plurality of electrical signals, and the processor may be further configured to: assign a weight to a model corresponding to the determined vowel in an authentication template, generate a characteristic value based on a first difference of magnitudes of the plurality of electrical signals, which is different from a second difference of magnitudes of the plurality of electrical signals used to determine the vowel, and recognize the speaker based on comparison between the characteristic value and the authentication template, in which the model corresponding to the determined vowel is as signed.

The processor may be further configured to assign the weight to the model corresponding to the determined vowel that is higher than a weight assigned to a model corresponding to another vowel.

According to still another aspect of an example embodiment, provided is a method of recognizing a speaker, the method including: receiving signals of a frequency band corresponding to a speech of the speaker; obtaining a difference of magnitudes of the signals; determining a vowel included in the speech of the speaker based on the difference of magnitudes of the signals; and determining whether the speaker is a registered speaker based on the determined vowel.

The determining the vowel may include: estimating relative positions of formants based on the difference of magnitudes of the signals; and determining the vowel based on the relative positions of the formants.

The receiving may include receiving the signals of the frequency band from a plurality of resonators having different resonance bands.

The determining whether the speaker is the registered speaker may include: assigning a weight to a model corresponding to the determined vowel in an authentication template; generating a characteristic value of the speaker corresponding to the speech of the speaker; determining whether the speaker is the registered speaker based on comparison between the characteristic value and the authentication template, in which the model corresponding to the determined vowel is assigned the weight.

The assigning the weight may include: assigning the weight to the model corresponding to the determined vowel to be higher than a weight assigned to a model corresponding to another vowel.

The weight assigned to the model corresponding to the determined vowel may be 1 and the weight assigned to the model corresponding to the another vowel may be 0.

