Target sound enhancement device, noise estimation parameter learning device, target sound enhancement method, noise estimation parameter learning method, and program

Patent metadata

Field	Value
Publication number	US-2020388298-A1
Application number	US-201716463958-A
Country	US
Kind code	A1
Filing date	Sep 12, 2017
Priority date	Dec 16, 2016
Publication date	Dec 10, 2020
Grant date	—

Abstract

A noise estimation parameter learning device is provided according to which even in a large space causing a problem of the reverberation and the time frame difference, multiple microphones disposed at distant positions cooperate with each other, and a spectral subtraction method is executed, thereby allowing the target sound to be enhanced. A noise estimation parameter learning device for learning noise estimation parameters used to estimate noise included in observed signals through a plurality of microphones, the noise estimation parameter learning device comprising: a modeling part that models a probability distribution of observed signals of the predetermined microphone, models a probability distribution of time frame differences, and models a probability distribution of transfer function gains; a likelihood function setting part that sets a likelihood function pertaining to the time frame difference, and a likelihood function pertaining to the transfer function gain, based on the modeled probability distributions; and a parameter update part that alternately and repetitively updates two variables of two likelihood functions, and outputs the time frame difference and the transfer function gain that have converged, as the noise estimation parameters.

First claim

1 . A target sound enhancement device, comprising:
an observed signal acquisition part that acquires observed signals from a plurality of microphones; a noise estimation part that associates an observed signal from a predetermined microphone among the plurality of microphones, a time frame difference caused according to a relative position difference between the predetermined microphone, a freely selected microphone that is among the plurality of microphones and is different from the predetermined microphone and a noise source, and a transfer function gain caused according to the relative position difference between the predetermined microphone, the freely selected microphone and the noise source, with each other, and estimates noise included in observed signals through a plurality of the predetermined microphones; a filter generation part that generates a filter based at least on the estimated noise; and a filtering part that filters the observed signal obtained from the predetermined microphone through the filter.

2 . The target sound enhancement device according to claim 1 ,
wherein the observed signal of the predetermined microphone includes a target sound and noise, and the observed signal of the freely selected microphone includes noise.

3 . The target sound enhancement device according to claim 2 ,
wherein the observed signal is a signal obtained by frequency-transforming an acoustic signal collected by the microphone, and a difference of two arrival times is equal to or more than a shift width of the frequency transformation, the arrival times being an arrival time of the noise from the noise source to the predetermined microphone and an arrival time of the noise from the noise source to the freely selected microphone.

4 . The target sound enhancement device according to claim 2 ,
wherein the noise estimation part associates, with each other, a probability distribution of observed signals of the predetermined microphone, a probability distribution where a time frame difference caused according to a relative position difference between the predetermined microphone and the freely selected microphone and the noise source is modeled, and a probability distribution where a transfer function gain caused according to the relative position difference between the predetermined microphone and the freely selected microphone and the noise source is modeled, and estimates the noise included in the observed signals through the plurality of microphones.

5 . The target sound enhancement device according to claim 4 ,
wherein the noise estimation part associates two likelihood functions set with each other based on three probability distributions and estimates the noise included in the observed signals through the plurality of microphones, the three probability distributions being a probability distribution of observed signals of the predetermined microphone, a probability distribution where a time frame difference caused according to a relative position difference between the predetermined microphone and the freely selected microphone and the noise source is modeled, and a probability distribution where a transfer function gain caused according to the relative position difference between the predetermined microphone and the freely selected microphone and the noise source is modeled, a first likelihood function being based on at least the probability distribution where the time frame difference is modelled, a second likelihood function being based on at least the probability distribution where the transfer function gain is modeled.

6 . The target sound enhancement device according to claim 5 ,
wherein the noise estimation part alternately and repetitively updates a variable of the first likelihood function and a variable of the second likelihood function.

7 . The target sound enhancement device according to claim 6 ,
wherein the variable of the first likelihood function and the variable of the second likelihood function are updated with an assigned restriction that limits the transfer function gain to a nonnegative value.

8 . The target sound enhancement device according to claim 7 ,
wherein the probability distribution of the time frame difference is modeled with a Poisson distribution, and the probability distribution of the transfer function gain is modeled with an exponential distribution.

9 . A noise estimation parameter learning device for learning noise estimation parameters used to estimate noise included in observed signals through a plurality of microphones, the noise estimation parameter learning device comprising:
a modeling part that models a probability distribution of observed signals of a predetermined microphone among the plurality of microphones, models a probability distribution of time frame differences caused according to a relative position difference between the predetermined microphone, a freely selected microphone and a noise source, and models a probability distribution of transfer function gains caused according to the relative position difference between the predetermined microphone, the freely selected microphone and the noise source; a likelihood function setting part that sets a likelihood function pertaining to the time frame difference, and a likelihood function pertaining to the transfer function gain, based on the modeled probability distributions; and a parameter update part that alternately and repetitively updates a variable of the likelihood function pertaining to the time frame difference and a variable of the likelihood function pertaining to the transfer function gain, and outputs the time frame difference and the transfer function gain that have been updated, as the noise estimation parameters.

10 . The noise estimation parameter learning device according to claim 9 ,
wherein the parameter update part comprises a transfer function gain update part that assigns a restriction for limiting the transfer function gain to a nonnegative value, and repetitively updates the variable of the likelihood function pertaining to the transfer function gain by a proximal gradient method.

11 . The noise estimation parameter learning device according to claim 9 ,
wherein the modeling part comprises: an observed signal modeling part that models the probability distribution of the observed signals with a Gaussian distribution; a time frame difference modeling part that models the probability distribution of the time frame differences with a Poisson distribution; and a transfer function gain modeling part that models the probability distribution of the transfer function gains with an exponential distribution.

12 . A target sound enhancement method executed by a target sound enhancement device, the target sound enhancement method comprising:
a step of acquiring observed signals from a plurality of microphones; a step of associating an observed signal from a predetermined microphone among the plurality of microphones, a time frame difference caused according to a relative position difference between the predetermined microphone, a freely selected microphone that is among the plurality of microphones and is different from the predetermined microphone and a noise source, and a transfer function gain caused according to the relative position difference between the predetermined microphone, the freely selected microphone and the noise source, with each other, and of estimating noise included in observed signals through a plurality of the predetermined microphones; a step of generating a filter based at least on the estimated noise; and a step of filtering the observed signal obtained from the predetermined microphone through the filter.

Assignees

• Nippon Telegraph & Telephone

Inventors

• Koizumi Yuma
• Saito Shoichiro
• Kobayashi Kazunori
• Ohmuro Hitoshi

Classifications

• G10L2021/02165

  Two microphones, one receiving mainly the noise signal and the other one mainly the speech signal · CPC title

• G10L21/0264

  characterised by the type of parameter measurement, e.g. correlation techniques, zero crossing techniques or predictive techniques · CPC title

• G10L21/0232 Primary

  Processing in the frequency domain · CPC title

• G10L2021/02082

  the noise being echo, reverberation of the speech · CPC title