0:00:14 | a morning everyone so um |
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0:00:16 | yeah even here from the intelligent robotic on number to read john and |

0:00:20 | that would present this |

0:00:22 | so |

0:00:23 | first this is just was introduction so we are interested in |

0:00:26 | separation problem like co but party problem where |

0:00:30 | so were a speaker are talking and there's a microphone array |

0:00:33 | so we we |

0:00:34 | consider |

0:00:35 | blind source separation |

0:00:36 | in the frequency domain |

0:00:38 | and we are in the permutation problem |

0:00:41 | and especially in the approach based on the direction of arrival so from which direction the signal coming |

0:00:47 | and a |

0:00:48 | we focus on the special i'm guessing |

0:00:50 | so what we it do we we show some model using the special a yeah thing |

0:00:53 | that we can maybe have some sparse solution and have to relate to this |

0:00:58 | the the permutation resolution problem |

0:01:01 | so this is a line of the talk so first us would talk about the |

0:01:04 | frequency domain blind signal separation |

0:01:08 | then |

0:01:08 | then the permutation problem |

0:01:10 | and after that that will go to talk about the mess with base |

0:01:14 | do you rate estimation |

0:01:19 | and the proposed approach so the specially in in equation of finding a solution and how to relate to the |

0:01:24 | permutation with |

0:01:28 | so first a domain mixtures so this is there is |

0:01:31 | very fast to tree so we have to |

0:01:33 | to people talking in front of the microphone array in the time domain to comparative mixture |

0:01:38 | if we you the frequency domain we have several set of |

0:01:42 | uh instantaneous mixture so here it was a future here we have much we see so we have a much |

0:01:46 | we see that give us |

0:01:48 | mixed to a mixed signal in each of the frequency bins |

0:01:53 | so |

0:01:54 | but still separation in one frequency bin is just finding actually a metrics that we |

0:01:59 | separate so weak over the signal so green and red here from the blue |

0:02:03 | one of the problem is that actually |

0:02:05 | when we do we |

0:02:06 | when we this is |

0:02:07 | using a |

0:02:10 | statistical independence like |

0:02:12 | independent component analysis |

0:02:15 | we have the permutation problem meetings that |

0:02:18 | we don't know |

0:02:19 | the mixed are so we don't know the order of the signal when we equal |

0:02:24 | a problem is that in uh |

0:02:25 | a domain approach |

0:02:27 | when we do all the processing so |

0:02:29 | we are in the frequency domain |

0:02:31 | we separate the mixture in each |

0:02:33 | of the frequency band |

0:02:35 | and at that we have to go back to time domain |

0:02:37 | so the premise that |

0:02:38 | usually we take the first signal is the first being as a first note is second be |

0:02:42 | and your which is a problem |

0:02:43 | if the order is different |

0:02:46 | we you have mixed signal |

0:02:47 | so meaning that |

0:02:48 | i'm addition resolution is just actually finding in each of the frequency being |

0:02:52 | a matrix matrix that we |

0:02:54 | or me the signal so that we exactly have or with |

0:02:58 | the right component to go back to time domain |

0:03:02 | so |

0:03:03 | there are many review you paper so this is one of them |

0:03:06 | that present a mini single about the convert source separation uh and also many single about |

0:03:11 | is a permutation problem so several ms what's of some miss database was or |

0:03:16 | on |

0:03:17 | checking the the signal that are separated |

0:03:19 | and some of the on the futures so that you can be in a station of the future some smooth |

0:03:23 | spectrum |

0:03:24 | using so directivity part N |

0:03:26 | or directly the direction of arrival so |

0:03:29 | here we are as a interest this five |

0:03:31 | i would also say that there is also some walk that was considering special i'm guessing |

0:03:36 | so only walk here for example |

0:03:38 | some of the work |

0:03:39 | based especially on the direction of arrival |

0:03:41 | and this walk |

0:03:43 | we we |

0:03:46 | so |

0:03:47 | here i |

0:03:48 | give some to on so miss what was a one based on direction estimation rate especially really to this |

0:03:56 | so |

0:03:57 | for simple we have a i was sick or a microphone array so the microphone a P P two P |

0:04:02 | three and we |

0:04:03 | i defined find some vector was actually for the position of the microphone |

0:04:06 | and here in a far-field assumption we have a a source that is coming from far |

0:04:11 | and |

0:04:12 | we have a vector of called here absolute do you way |

0:04:14 | that is actually |

0:04:16 | showing the direction from weight can scope |

0:04:18 | we can have actually a a direct bus more that of the mixture |

0:04:22 | in that |

0:04:23 | each of the colour not the mixing matrix is actually |

0:04:26 | the steering vector or corresponding |

0:04:28 | to the direction |

0:04:29 | from we just rolls is coming like here |

0:04:31 | so we see |

0:04:32 | the |

0:04:33 | uh we see a |

0:04:36 | so this is a microphone vector or as was on this is actually just ring vectors so this scroll on |

0:04:40 | this on the you one |

0:04:42 | these one source of a column on the one depending on different |

0:04:45 | during vector |

0:04:46 | when we do the separation actually |

0:04:48 | we recover |

0:04:50 | the match that when we inverse it we have a and to make |

0:04:53 | we can have an estimate of these and the problem of permutation |

0:04:56 | is actually that |

0:04:57 | if those are steering columns that would be steering column |

0:05:00 | which are muted meaning that |

0:05:02 | here for example this |

0:05:04 | for vector |

0:05:05 | is not the first one it can be wanting to me |

0:05:07 | so |

0:05:08 | here is how the permutation appear on this and the colour of the separated met |

0:05:14 | so |

0:05:15 | actually knowing this we can |

0:05:17 | this so this is a paper |

0:05:19 | from a |

0:05:19 | somewhat a |

0:05:21 | i a key mckay |

0:05:22 | lacking of sound |

0:05:23 | it's a |

0:05:25 | we can see do the |

0:05:26 | the racial of the element in the colour on |

0:05:29 | to get |

0:05:30 | actually is these but so we see that |

0:05:32 | this we should know because you is |

0:05:33 | so microphone we know the position |

0:05:35 | and this is up to G away |

0:05:37 | actually if we are know in a region as of argument function |

0:05:41 | to G some meaning that Z is for example in minus spy |

0:05:44 | i |

0:05:45 | then |

0:05:46 | we can we call work Q |

0:05:48 | from the racial of the and so the constraint that it put on the sense or is also that |

0:05:53 | actually |

0:05:54 | he so this is mainly the distance between some sense as and this is absolute do you a |

0:05:58 | and this is more or less and angle between so |

0:06:01 | and for the actual do used like used and and go |

0:06:04 | between this vector |

0:06:06 | and this one |

0:06:07 | and depending on this angle for different frequency for them for for low frequency to people are |

0:06:12 | and |

0:06:13 | actually we we have a and yeah one we are over |

0:06:16 | when we have a spacing between the microphone |

0:06:19 | that is over the blue curve and its independent of the angle between those two |

0:06:23 | if we have a linear rates very easy |

0:06:26 | but for a cherry or a have for the first check or or or or even a |

0:06:29 | different form |

0:06:30 | is not so easy to know which pair we have |

0:06:33 | some ideas in because we don't know usually Q |

0:06:35 | so meaning |

0:06:36 | and if the frequency of meant we see that |

0:06:38 | the sense so has to be really close |

0:06:41 | same |

0:06:41 | for some fixed |

0:06:43 | send so this stance so for fixed microphones some distance between the sense or |

0:06:47 | we can actually |

0:06:48 | we have also limits still up to the blue curve for twenty sent to meet that will you have |

0:06:52 | and the in so for frequency or or |

0:06:55 | some value and depending on the angle |

0:06:57 | so the thing here is that |

0:06:59 | when we have a |

0:07:00 | a linear rate |

0:07:01 | and we can just the |

0:07:04 | smaller a pair |

0:07:05 | these these are |

0:07:07 | these are constant |

0:07:08 | but but we have we may have an array a to send you to always |

0:07:12 | but for a a or real rate maybe we want |

0:07:14 | we may have a |

0:07:15 | using this power can use this all the per |

0:07:18 | this one this one they have very different |

0:07:20 | distance |

0:07:24 | you there is no using a a good solution that was proposed is actually to start |

0:07:28 | or is a value for the column |

0:07:30 | and to stack all the position or a to make a a big uh matrix |

0:07:34 | and we we get this kind of equations where i will |

0:07:38 | the |

0:07:39 | direction of a right but we want to find should do the solution and |

0:07:42 | we can have at least squares solution so this is still |

0:07:44 | so walk with somewhat what was a also |

0:07:47 | oh |

0:07:48 | and so why do we do that is that |

0:07:50 | we |

0:07:51 | estimate |

0:07:52 | we |

0:07:52 | blind just suppression some matrices |

0:07:55 | from there we can get some direction of arrival |

0:07:57 | and |

0:07:58 | if we see for the different frequencies the direction of a right so this is |

0:08:01 | the permutation we see that in this |

0:08:04 | a C is a for example the first component it's coming from |

0:08:07 | sometimes so the blue is a first component it maybe coming from this direction |

0:08:12 | was this direction sometimes actually if we are able to seize direction |

0:08:15 | and |

0:08:16 | permit attack to that |

0:08:17 | we will so the permutation problem |

0:08:21 | oh |

0:08:22 | here are in this paper we i interest in the case where they're especially i'm guessing meaning that |

0:08:27 | this relation |

0:08:28 | for some frequency else for some sense so pair is not |

0:08:32 | it's not longer very fine |

0:08:33 | so meaning that actually |

0:08:35 | we can introduce a some values so this are in take it actually those in check your |

0:08:40 | so that we have this relation the |

0:08:43 | this is not true but this one is true we put some that have a you here so that this |

0:08:47 | one is two |

0:08:47 | so to show eight for example for frequency of |

0:08:50 | two thousand hz and |

0:08:52 | one sickle a rate |

0:08:54 | this is actually |

0:08:55 | so more less the distance between the microphone and the angle between |

0:08:59 | so a |

0:09:01 | vector |

0:09:02 | between the two microphone and the absolute do way |

0:09:05 | so in red |

0:09:06 | we have |

0:09:07 | this |

0:09:08 | here |

0:09:10 | okay okay |

0:09:10 | so we see that it's over |

0:09:12 | P and minus P and undermine the P |

0:09:15 | so these are the |

0:09:16 | but you in take a value |

0:09:18 | so but you by by to by |

0:09:20 | that we have to add |

0:09:22 | the green curve |

0:09:23 | and this is actually the difference of the two that is always |

0:09:27 | in the boundary |

0:09:28 | so this actually |

0:09:29 | this one the press this one gives this |

0:09:33 | oh |

0:09:34 | we can also add this |

0:09:35 | to the racial of the call on meaning that we have to those term as before but it also a |

0:09:40 | this |

0:09:41 | uh |

0:09:42 | difference is in figure here |

0:09:44 | so if we stack |

0:09:46 | the same way those resort |

0:09:47 | we also get and |

0:09:49 | equation that should be verified |

0:09:51 | by a known direction of ball but also |

0:09:55 | we have those |

0:09:56 | in a value that appear in the second part C a and here's was value also unknown no |

0:10:01 | a tree if if there is no single like this |

0:10:04 | this would be this is it's simple miss we with special and this |

0:10:09 | so |

0:10:10 | so here is just to show that uh |

0:10:12 | we can transform this equation question with a Q and that of that appear we can transform it actually to |

0:10:17 | would be to a equation that is only we i'd |

0:10:19 | by this down that |

0:10:21 | so yeah yeah change of bits and the patients as the first part here i've we name it G G |

0:10:26 | yeah |

0:10:27 | it depend actually |

0:10:29 | of this |

0:10:31 | but use |

0:10:33 | which we can see depend |

0:10:35 | on the |

0:10:37 | estimated things |

0:10:38 | from the metrics so it you and of the |

0:10:41 | colour on so G and of the frequency |

0:10:44 | this part |

0:10:44 | C |

0:10:45 | here |

0:10:46 | is just |

0:10:48 | depending of the sense geometry and see every name E |

0:10:51 | this one i mean |

0:10:52 | you we see later Y |

0:10:53 | so we have this equation |

0:10:56 | oh |

0:10:58 | the proposed so think is that we would like to solve as a question and |

0:11:02 | to find actually a what delta |

0:11:04 | the things that this equation depend we have a a actually the symmetric is not for run so that is |

0:11:09 | an infinite number of solution |

0:11:11 | we can |

0:11:12 | for example simple get a solution with a minimal norm like this |

0:11:16 | but we have a our interest in an indigo solution to the equation |

0:11:20 | which is different from this one show |

0:11:24 | so |

0:11:25 | i was talking about sparsity also in the introduction because actually |

0:11:30 | we can know that this that that |

0:11:33 | G |

0:11:33 | have a new and trees |

0:11:35 | for the rows that correspond to |

0:11:37 | microphone pair without and the other thing for the given frequency |

0:11:41 | so it means that |

0:11:42 | if we have a good initial guess but i'm pretty phi can have a initial guess like is this |

0:11:47 | the difference between this initial guess |

0:11:50 | and the value "'em" searching should be sparse so |

0:11:52 | here have for an example |

0:11:54 | that's say that |

0:11:55 | i mean rest in |

0:11:56 | so frequency |

0:11:58 | two thousand and |

0:11:59 | one hundred hz and they used to seven hz one for guess |

0:12:03 | so these are actually here |

0:12:05 | that that that |

0:12:06 | in green |

0:12:07 | so |

0:12:08 | and they quite similar so if we look as the difference the different is nearly always with zero |

0:12:12 | except for some value so it's are like to be them the one |

0:12:17 | well yeah i mean interest in Z is |

0:12:19 | actually because |

0:12:21 | we want to tree to like in many at the reason that solve the permutation we get we start from |

0:12:26 | the lower what frequency where a less permutation and we |

0:12:30 | or to higher frequency to sort of them so he the same we we |

0:12:33 | we use the previous |

0:12:34 | frequency be as a meaning that |

0:12:37 | for the been G |

0:12:39 | of for the bin F |

0:12:40 | at the can and J we use the result we got for the previous B and we start from the |

0:12:44 | low work |

0:12:45 | for each case we be so for a what a question so |

0:12:48 | with the initial guess |

0:12:50 | here |

0:12:51 | and this is actually a re the solution so the the real solution of is minimal no |

0:12:55 | then we take actually is the rounding of distribution to have |

0:13:00 | to have an intake |

0:13:01 | and the goal is actually we would like to have this X close |

0:13:04 | to the indigo so that that were rounding give this it |

0:13:08 | this is why actually |

0:13:10 | we were trying to have this initial guess that is close |

0:13:14 | quite spots |

0:13:15 | so |

0:13:16 | this is and |

0:13:17 | oh first approach S i guess a it's in better solution to find a sparse |

0:13:22 | direct you sparse solution to this the question but |

0:13:25 | i i didn't the E D |

0:13:27 | so |

0:13:28 | when we have a solution that to we can define the residual which use actually how good the question was |

0:13:32 | source to this is just actually |

0:13:34 | the difference between |

0:13:36 | uh |

0:13:37 | the solution of the question |

0:13:39 | and uh well |

0:13:41 | what is the error |

0:13:42 | of that |

0:13:44 | uh a what where steep |

0:13:46 | so |

0:13:47 | how do i realise is to permutation resolution |

0:13:50 | it simply that |

0:13:52 | when we are |

0:13:53 | moving from the frequency being F minus one to the frequency F |

0:13:58 | you there is a permutation say of the column K |

0:14:01 | and G |

0:14:03 | so |

0:14:04 | in the |

0:14:05 | been F we we use this equation some innings that |

0:14:08 | we want to solve this equation to find X |

0:14:11 | here |

0:14:11 | that is solution of this which question we see that |

0:14:14 | we are in the row K |

0:14:15 | so |

0:14:16 | what the column catch |

0:14:18 | and so we have here |

0:14:20 | the K index but because of the permutation here |

0:14:23 | we will be using |

0:14:25 | the guess from that correspond to a knows or colour |

0:14:28 | chip |

0:14:29 | so |

0:14:30 | if is two solution |

0:14:32 | for the current J and K are quite different |

0:14:35 | we would not find a closing take a solution |

0:14:37 | meaning that the residual so the error or on the equation |

0:14:40 | would be large |

0:14:42 | so |

0:14:42 | how large |

0:14:43 | this we depend also of how much uh a noise there is no what estimate meaning |

0:14:48 | uh if i where bss it's the walk where on not |

0:14:51 | so |

0:14:52 | we can of the first way would be to compare as residual to a threshold |

0:14:56 | decide if that was a permutation on not |

0:14:58 | but this is not so easy because |

0:15:00 | of the noise finding this threshold is not is |

0:15:03 | and as a solution is |

0:15:05 | we did this for the row K we can do for the road change so we we have another reason |

0:15:09 | you |

0:15:10 | or with |

0:15:11 | and X K and compares the to to decide if there was a permutation on not this will be a |

0:15:15 | seem you know to was a ms so that compare |

0:15:18 | uh the direction of a right |

0:15:20 | the problem is that some |

0:15:22 | when especially when the absolute |

0:15:25 | direction of arrival for the colour a quite close |

0:15:28 | so as to value may be close meetings that actually |

0:15:31 | even |

0:15:32 | the the reason you're be small so we we not detect the permutation |

0:15:36 | just make the read you are in such case |

0:15:38 | we have actually to compute |

0:15:41 | here |

0:15:42 | so absolute you way |

0:15:45 | we we have to compute that it'd the U A and try to use a |

0:15:47 | this up to do you a |

0:15:49 | with the one from the previous frequency to so |

0:15:51 | this problem |

0:15:52 | so in this case the mess what got to bit |

0:15:54 | close a tools or pro |

0:15:57 | so |

0:15:59 | when we can see the |

0:16:00 | uh for so this is the kind of post processing to solve this problem we first consider a all the |

0:16:05 | frequency bins where a all the row we have small residual |

0:16:10 | meaning that |

0:16:11 | we we did that all the frequency be and we can see that or the one for which |

0:16:15 | we had directly |

0:16:17 | small residual |

0:16:18 | for these we estimate |

0:16:21 | the sum absolute doa is |

0:16:23 | we have a this absolute you always along the frequency |

0:16:27 | and for or the are as and |

0:16:29 | we compare |

0:16:30 | so |

0:16:30 | estimated you eight to this average about you and do the clustering according to |

0:16:35 | so this is very similar ads |

0:16:37 | a to be to the a approach |

0:16:38 | where you find some direction of a one and you close to the |

0:16:44 | so |

0:16:45 | here i i haven't for that then the lee and you now one D |

0:16:48 | some simulation results once to make the data |

0:16:52 | where we can see there are sixteen microphone |

0:16:54 | uh a a race was sick or microphone so |

0:16:56 | the drawing that was before |

0:16:58 | it has a diameter of thirty thirty for one cent to majors |

0:17:01 | so we can see sixteen Q has something frequency and five hundred to |

0:17:05 | fifty |

0:17:06 | so this is how i model that of is estimated colour |

0:17:10 | so we have |

0:17:11 | here |

0:17:12 | oh this would be the problem if they don't not |

0:17:14 | uh absolute do way |

0:17:16 | so like these |

0:17:17 | and i put some error or so |

0:17:19 | on the angle |

0:17:21 | that is |

0:17:21 | that are uniform in gamma |

0:17:23 | in a |

0:17:24 | in uh |

0:17:26 | as they are uniform on the |

0:17:29 | interval mine got come model so meaning that a some error or on the direction of arrival |

0:17:35 | and there is also some at know |

0:17:37 | for |

0:17:37 | showing the error or the estimation of this one |

0:17:41 | and |

0:17:42 | for some of the frequency |

0:17:43 | so a random permutation of the core of the core and the percentage |

0:17:47 | they |

0:17:48 | D of these frequency bins uh |

0:17:51 | permit it |

0:17:52 | so how about we measure the performance |

0:17:54 | is |

0:17:55 | first |

0:17:56 | the present age of frequency been with adequate permutation after part |

0:18:00 | after the processing |

0:18:02 | and also as ever all |

0:18:03 | on the absolute there or do you a |

0:18:06 | estimation |

0:18:07 | so i that is to experiment vector in the first one we try to see in france |

0:18:11 | of the different |

0:18:12 | a parameter |

0:18:13 | so |

0:18:15 | the additive noise |

0:18:17 | the a row and the end goal |

0:18:19 | and that |

0:18:20 | is um the racial of for a permit it |

0:18:23 | uh call |

0:18:25 | and the second experiment |

0:18:26 | i'm right and this is done for some fixed the absolute do you a and |

0:18:30 | we have a rate the resort to a and some uh |

0:18:32 | a certain number numbers |

0:18:33 | independent run |

0:18:35 | the second |

0:18:36 | experiment |

0:18:37 | we want to actually |

0:18:39 | okay so this is Q to actually |

0:18:41 | we see we want to see the difference between |

0:18:43 | is the angle between the absolute to you a how it's |

0:18:46 | it seems finance |

0:18:47 | on the result because |

0:18:50 | this is critical especially |

0:18:52 | "'cause" |

0:18:53 | this is what create this kind of problem |

0:18:59 | so this is a result of the first experiment so |

0:19:02 | first |

0:19:04 | one case we just compare the residual so meetings that there is no prob |

0:19:07 | post processing we just compare the with you're we don't compute a |

0:19:11 | uh |

0:19:12 | here in this case we don't compute any direction of rival to result |

0:19:16 | the |

0:19:16 | to resolve the permutation the second case |

0:19:19 | we actually do the post processing that much |

0:19:21 | propose that |

0:19:23 | we |

0:19:23 | in this |

0:19:24 | we make a second pass |

0:19:26 | to get |

0:19:27 | the direction of arrival to permit the beans that maybe had a |

0:19:30 | so |

0:19:31 | it's a first call and here we see actually |

0:19:34 | that |

0:19:34 | this is a in france of that the even noise |

0:19:38 | okay okay |

0:19:39 | and |

0:19:40 | on the permutation ratio and |

0:19:42 | on the or on the deal so we see act actually |

0:19:45 | uh |

0:19:46 | that is an improvement when we do |

0:19:48 | uh the post processing |

0:19:50 | for the number of limitation that the result and |

0:19:53 | and T it's quite constant and you |

0:19:56 | a set and |

0:19:56 | i'm not of uh it's quite robust yeah to the |

0:19:59 | at no |

0:20:00 | in the second experiment |

0:20:02 | we we see the in france of the air or on the angle of that you way |

0:20:06 | so no |

0:20:07 | how there is this dispersion of that do you S so this would be the case in a room where |

0:20:10 | there is more rubber break more less reverberation |

0:20:14 | so |

0:20:15 | we see that for this one same |

0:20:17 | and you a and there were all of around the |

0:20:20 | fifteen degree they is not so much decrease but that does that we see a sharp you decrease meaning that |

0:20:25 | it's quite sensitive so |

0:20:26 | this may be a problem |

0:20:28 | for high reverberant room |

0:20:31 | in the third colour on we see actually |

0:20:33 | so different uh |

0:20:35 | amount of permit date |

0:20:36 | uh |

0:20:37 | a column before processing so |

0:20:39 | how we can friends a result so we see that |

0:20:42 | with a post processing it's quite clean |

0:20:44 | well as |

0:20:45 | it decrease faster are really with no post processing that meaning that |

0:20:48 | the more corn and we have to that that the less |

0:20:50 | good we are at |

0:20:52 | uh something the or where as it's quite a linear so |

0:20:56 | and same so what so ever and go to increase very fast with the post |

0:21:02 | oh |

0:21:02 | the second experiment is actually we have the different of us so this is the angle between |

0:21:07 | is a two steering vector corresponding to the colour on |

0:21:11 | and we see how this in france the mess it so the first thing is that in this case |

0:21:15 | so two curve a very different meanings that |

0:21:17 | without |

0:21:18 | the if we just use the residual |

0:21:20 | so |

0:21:21 | we don't |

0:21:22 | we don't try to use |

0:21:23 | to get is up to you the and self |

0:21:25 | we need actually to have absolute the you a that that separate separated to to reach |

0:21:29 | uh |

0:21:31 | acceptable results |

0:21:32 | so meaning like |

0:21:33 | there should be at least thirty forty T we between them whereas |

0:21:37 | with a post processing |

0:21:38 | this is not the problem we and Q fifteen degrees here it was to walking |

0:21:42 | okay |

0:21:45 | so |

0:21:46 | to compare that would say that we we consider this problem and the case of special i'm guessing |

0:21:51 | we we introduce a kind of model for the special at using to solve the permutation so |

0:21:55 | one thing that has to be done in sector is now my solution to the equation so to find my |

0:22:00 | sparse solution it's a |

0:22:01 | uh how to say |

0:22:03 | a very easy approach that maybe some that to to do |

0:22:06 | and of course to apply these to real data and compare it with is was of missile |

0:22:19 | we have time for only |

0:22:20 | one |

0:22:21 | question |

0:22:29 | okay |

0:22:30 | thank |