i

but

thank you

and

the work has been carried out uh and good morning and the work has been carried out uh in the

department of electrical and computer engineering at the university of buttons in greece

by a at yeah your run D professor them would open as and my sense

and uh the work is on the binaural extension of

single-channel channel spectral subtraction

reverberation i'm

reverberation has been a challenging research is you for at least forty kate

and

now the verb techniques are applied either there are standard as standalone process

in order to enhance the reverberant signals quality

or even uh increase this reverberant speech intelligibility

or or as preprocessing steps before other several signal processing algorithms and applications in know the to increase their performance

and one one is developing uh binaural dereverberation algorithms

uh it should also take into account some constraint

that are imposed from the binaural aspect of the or a system

so as we all know um when the sound that i've in the left and that a right E channel

here

of the listener

it does as with a relative delay and the relative late uh level different

and these so-called binaural cues are important for the localization of

sound the sound space

and this should definitely be preserved from the binaural signal processing in general or

and more specifically for the binaural from the binaural dereverberation algorithms

on the other hand binaural reverberation

has very appealing applications

it can be applied in hearing aids

in binaural telephony in hands-free devices

in most of the code

a telecommunications

so uh recently we have proposed in our lab uh some single channel dereverberation algorithms

we have proposed a framework for improving single-channel channel existing spectral subtraction dereverberation algorithms

we have also uh presented a novel method um of high computational complexity that gives

uh perceptual sick need

perceptually good results

which is based on perceptual reverberation modeling

and also a fast uh semi-blind reverberation with

that's which is based on the hand club recording

which targets

speech application

so

the state for what step for us was to extent

uh sets a technique and the binaural context

and

and

the most of those uh thing to do was to extend uh the spectral subtraction dereverberation which is

uh techniques of low computational complexity when compared to sophisticated

and what that the remote pro

so the specific gains of this work

uh is to propose a single frame frame for the extension of single-channel channel spectral subtraction dereverberation algorithms

two

uh into use and efficient way

to prevent of estimation errors

and also to evaluate the proposed framework in several state-of-the-art spectral subtraction dereverberation technique

um

expect that subtraction was originally proposed for D knows in application

but recently it has been applied for the suppression of late reverberation

we all know in room acoustics that after the direct sound

the L reflections are i've these are discrete echoes that come from the close surface and produce spectral

uh degradation that is perceived as colouration

in the diffuse feed the late reverberation arrives

which has a the gang noise or a like characteristics

and he's perceived as the well-known signal a reverberant tails

so in the late reverberation suppression some context spectral subtraction

uh gives the any coke estimation by simply um subtracting from the reverberant signal and and then uh and uh

estimation of late variation

and mostly liberation separation methods that work can this way

how to uh estimate exactly these late reverberation spectrum more power spectrum depending on the method

and let's look some state-of-the-art methods

yeah

the methods proposed by where wine gone for we can cut out come from a one will refer to them

as W W an S K A

i i taking someone assumptions on the reverberant signals that these six

while the well known uh reverberation technique from bar to and then be

uh uh from oh no we refer to this as a B

is um a concern assumption on reverberation characteristic

keep in mind that

we can easily express the subtraction um

a principle as again multiplication

uh in the frequency domain by deriving the appropriate gain

so the

a straightforward approach would be to implement separately in the binaural context uh independently this uh late reverberation suppression technique

for the left and the right channel

but it has been proved that the lateral signal processing will destroy this binaural cues and

uh it will make the localization in the produced signal uh be distorted so

and in the bibliography

be i hitting a can team has proposed

uh spectral subtraction extension which is based on the delay and sum beamformer

uh

by beamforming by actually at thing at the left and the right the channels and synchronizing then

um

it produces a reference signal it then makes the late reverberation estimation and the signal and then it apply spectral

subtraction independently

uh in the left and the right yeah

and so the binaural cues are present

in these work

uh i will make an extra samson that the relative delay between uh that to um E S i actually

depends on the weight of the human head and

it can be assumed that it would be uh smaller than the typical analysis windows

so we for this work uh we meet the delay and sum beamformer state

and we propose a binaural extension which is based on a single channel uh spectral subtraction dereverberation on

based and lateral again of station

a see the signal flow of the proposed approach

uh

separately from the web left and the right a rubber and frames with the two different estimations

and uh know the to derive the bi lateral games

then these gains are combined

with a chosen a again of the patient seen

in order to to give us the binaural game

then

again my to the regularization seem that prevents from of very estimation roles that we introduce here is applied

in order to give us a constraint binaural again

which is separately independently

applied on the left and the right frame

the gain adaptation for the gain adaptation in this work was chosen the or to use uh started is

by taking the marks again in it's frequency being uh we had seemed more it's operation and fewer processing artifacts

by taking the average gain would be the compromise between the reverberation reduction and the processing folk

while the minimum gain give significance of print so oppression but

it can be easily introduce artifacts

so the selection of the gain of the patients one was made according to the application scenario

you know there

these blind method as are uh use and introducing uh signal artifacts and to not to to prevent from such

of estimation not different

um

we have

uh probe proposed here we introduce here again a market to the regularization step

which is implemented

uh in the low signal to reverberation or should detector

the assumption here is that um

musical noise or yeah other of estimation that the facts

will a um

we are more probably to uh be present in low signal to reverberation racial frames

and this these and didn't regularization sing

uh depends on a regularization application of to see that

and

on a regularization ratio are

these are user defined parameters that can be a just

in order to um control the suppression rate

so this that um

while properly uh just adjusting these parameters can compensate for estimation error

and prevent musical noise

further explain uh the use of these parameters

these are typical spectral gain functions

and now by keeping seat that to zero point two and are equal to

uh are equal for an a equal or are equal eight we can see how the gain functions

saying

and

but keeping think to uh uh are constant we can change the

two zero point four and zero point sick

so we

from here we can see that a that can be used for the but note um

control of the separation range

why of the parameter R can be used for fine tuning the method

uh let's present some results

uh these results

um

are uh um made with um measure at um

i impulse responses

these uh a specific uh a is since a given from the i can that the base yeah that the

base

in the stairway away for uh with a reverberation time of

zero point seven approximately

note the to evaluate the results

uh we used to metrics the signal to reverberation

or a should difference when compared to the reverberation

to the reverberant signal

so pos difference is be note that the um

more significant reduction

and also um medic the pesq Q uh difference when comparing to the reverberant signal

which relates more to the perceptual

uh quality of the final result

uh we implement

uh this

three by a binaural gain adaptation the patient started is

as well as a delay and sum beamformer or in three state of the art a spectral subtraction dereverberation algorithms

V L B W W gone of gay

and as we can see

uh all of the then any can me significantly reduce reverberation

as we expected the mean gain adaptation seem we'd uses more reverberation while the marks gain less

and when seeing the

where P Q difference which makes more sense in a from a perceptual point of view we can see that

the W W method with the mean game technique

uh gives slightly but the results

these results are taken in the at the uh from the all the would that the base

and

these cafeteria has uh

high reverberation time of one point three seconds

and um

ooh

as we can see that is the reverberation reduction here is um

smaller

and it seems that

such techniques in the sets reverberant conditions

uh and enhance the final signals

but on the other hand uh the enhancement is less than the previous case

again uh the W W to can uh technique i had achieved uh but the results

in terms of

um S R are and press

and uh the best results were uh were observed for the average gain adaptation seen

so we not there to presents some further evaluation we conducted

um

subjective evaluation test

this test was based on the I T U B

eight thirty five and recommendation

and

seventeen test subjects participated in the test

uh we made by a look test not the to get to test the um two

choose the best of the station

and seem for the set it's techniques so for the L B and W W technique

the average gain adaptation was chosen while for the S T A an meaning i the M meaning gain technique

was chosen

and the test subjects were asked

two or rate the speech not real nice

they reverberation intrusive an S and the overall quality of

this speech signals

um

for a in a most K from zero to five

so from these results

we can see that uh the test subjects

rate the dereverberated signal

i net less natural in all cases

however

and we notice a significant reverberation reduction

and also

at least the L B and W W techniques preserve the signal quality the overall signal while

and a for gently we need

um

headphones phones know the to diffuse some them one

but if anyone is interested

uh that then was out of a are available in the web of our group

um B website is also in the paper uh is written in the paper

so to sum up

and

we have introduced a framework for five binaural spectral subtraction dereverberation

which is based on bi lateral gain adaptation

the gain map and the regularization seeing that we introduced can read use the over estimation errors

and produce some uh uh and

um

preserve

from some uh

uh the gradations uh processing the gradations

the selection of the adaptation seem and the D M parameters

uh can be made according to the application scenario

and there is also significant reverberation reduction

uh while the overall speech quality and the binaural cues are

can be present

how there

we noticed some loss of speech naturalness

so for the for us this indicates the need for native binaural mode it's

models that take into account the binaural properties of the to the system

and

this is on what where working right now

thank you very much

okay um we have time for a few questions

you that questions can you just use the microphone over there

any questions from the audience

and questions

okay maybe i just start

okay a how do you

oh man on the uh uh the accuracy of this been all real

oh and uh cues preservation

uh this is a big problem because actually we

the a perceptual test

that can and exactly and um

read the of on the on these

these need to really control the um

and um

environment

and so it was really difficult to do so it's that's actually

uh i think that i i'm not aware of uh and it test for reverberation a graph that

and and um

uh exactly uh predict the these

uh binaural cues preservation

um this is the for the for further investigation

so you have not done any subject you test on this

on these snow

the questions

you know we best you really

uh

another question is how do you did the mean this power meters

you know G R G M R

or

uh

these parameters

actually depend on the frame length

and on the reverberation time on how to store to this you not signal

and we give some uh range for the parameters in the paper

so

uh

actually the they are

different frequencies range

for it's sampling frequency needs frame length

that's the user can that know the to take the optimal results

so for your experiment or for simulations are a bit sorry

use no we made by look test

to tune the parameters

for these

a rules what different environments yes

any questions

so you've not last thanks the speakers again