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9ff7c123db26184b9df045dec05e6c7464806627
ami
AMI_EN2001a_H04_MEO069_0330297_0330718
If you if you S. S. H. and they have this big warning about doing nothing at all in the gateway machine
IF YOU IF YOU S. S. H. AND THEY HAVE THIS BIG WARNING ABOUT DOING NOTHING AT ALL IN THE GATEWAY MACHINE
gpt-5.6-luna
MEO069
MEO069
4.209961
3,302.969971
3,307.179932
AMI_EN2001a_H04_MEO069_0330297_0330718
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
0
f37455ce50962dee0831fc428d44bc546d4f383d
ami
AMI_EN2001a_H00_MEE068_0414915_0415078
I've gotten mm hardly any
I'VE GOTTEN MM HARDLY ANY
gpt-5.6-luna
MEE068
MEE068
1.629883
4,149.149902
4,150.779785
AMI_EN2001a_H00_MEE068_0414915_0415078
EN2001a
H00
null
null
null
null
null
null
null
train-00000-of-00042.parquet
1
c4e2de2a8a5fd693ab082c79823763a65ecb3d0a
ami
AMI_EN2001a_H03_MEE067_0319290_0319815
It's yeah I mean the wave data are obviously not gonna get off there completely
IT'S YEAH I MEAN THE WAVE DATA ARE OBVIOUSLY NOT GONNA GET OFF THERE COMPLETELY
gpt-5.6-luna
MEE067
MEE067
5.25
3,192.899902
3,198.149902
AMI_EN2001a_H03_MEE067_0319290_0319815
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
2
dfa3bd9291753e8f35528c1aad1d7f7d86883350
ami
AMI_EN2001a_H04_MEO069_0145515_0146152
Yeah it'll it'll play them in some order in which they were set because otherwise it's gonna be more entertaining
YEAH IT'LL IT'LL PLAY THEM IN SOME ORDER IN WHICH THEY WERE SET BECAUSE OTHERWISE IT'S GONNA BE MORE ENTERTAINING
gpt-5.6-luna
MEO069
MEO069
6.369995
1,455.150024
1,461.52002
AMI_EN2001a_H04_MEO069_0145515_0146152
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
3
e622a4ebdb367daa93de825f97e47f120f7fa5d2
ami
AMI_EN2001a_H03_MEE067_0478127_0478164
Yeah
YEAH
gpt-5.6-luna
MEE067
MEE067
0.370117
4,781.27002
4,781.640137
AMI_EN2001a_H03_MEE067_0478127_0478164
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
4
66e38f97e3258459193d07aaffb92a9e2de6509d
ami
AMI_EN2001a_H02_FEO065_0436920_0436957
Hmm
HMM
gpt-5.6-luna
FEO065
FEO065
0.369629
4,369.200195
4,369.569824
AMI_EN2001a_H02_FEO065_0436920_0436957
EN2001a
H02
null
null
null
null
null
null
null
train-00000-of-00042.parquet
5
dac7ae4374a6ea73dbb8d13246c5a892f1927595
ami
AMI_EN2001a_H04_MEO069_0171941_0172087
All these fancy pens
ALL THESE FANCY PENS
gpt-5.6-luna
MEO069
MEO069
1.459961
1,719.410034
1,720.869995
AMI_EN2001a_H04_MEO069_0171941_0172087
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
6
f7ff00b0fdd154acbcf4d761c305488bce1026d9
ami
AMI_EN2001a_H04_MEO069_0122764_0123754
Like something that represents the whole series in in a V in a structure very similar to the structure in which we represent individual um meetings
LIKE SOMETHING THAT REPRESENTS THE WHOLE SERIES IN IN A V IN A STRUCTURE VERY SIMILAR TO THE STRUCTURE IN WHICH WE REPRESENT INDIVIDUAL UM MEETINGS
gpt-5.6-luna
MEO069
MEO069
9.900024
1,227.640015
1,237.540039
AMI_EN2001a_H04_MEO069_0122764_0123754
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
7
ef353591cb090679859a27f83a94995fd2855d82
ami
AMI_EN2001a_H03_MEE067_0368111_0368920
'Cause if we're gonna allow disjoint segments for example then how are we gonna know what's gonna be in context at any given time
'CAUSE IF WE'RE GONNA ALLOW DISJOINT SEGMENTS FOR EXAMPLE THEN HOW ARE WE GONNA KNOW WHAT'S GONNA BE IN CONTEXT AT ANY GIVEN TIME
gpt-5.6-luna
MEE067
MEE067
8.089844
3,681.110107
3,689.199951
AMI_EN2001a_H03_MEE067_0368111_0368920
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
8
5bdb91d1028ee391e0f8830117aa9abc082ebeb2
ami
AMI_EN2001a_H04_MEO069_0292554_0293396
Is anyone of you for the for the document frequency over total frequency you gonna have total frequencies of words then with that right
IS ANYONE OF YOU FOR THE FOR THE DOCUMENT FREQUENCY OVER TOTAL FREQUENCY YOU GONNA HAVE TOTAL FREQUENCIES OF WORDS THEN WITH THAT RIGHT
gpt-5.6-luna
MEO069
MEO069
8.419922
2,925.540039
2,933.959961
AMI_EN2001a_H04_MEO069_0292554_0293396
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
9
eda4eafec8ce4e78b2399788f570422853163009
ami
AMI_EN2001a_H03_MEE067_0296353_0296603
Like I don't know copies of Shakespeare or something
LIKE I DON'T KNOW COPIES OF SHAKESPEARE OR SOMETHING
gpt-5.6-luna
MEE067
MEE067
2.5
2,963.530029
2,966.030029
AMI_EN2001a_H03_MEE067_0296353_0296603
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
10
5461bc12494f72d9338359a187426bc0eccdb0cd
ami
AMI_EN2001a_H02_FEO065_0081159_0081631
I'm not quite so what it did you want to do it I you just wanted to assign
I'M NOT QUITE SO WHAT IT DID YOU WANT TO DO IT I YOU JUST WANTED TO ASSIGN
gpt-5.6-luna
FEO065
FEO065
4.719971
811.590027
816.309998
AMI_EN2001a_H02_FEO065_0081159_0081631
EN2001a
H02
null
null
null
null
null
null
null
train-00000-of-00042.parquet
11
d7c397423074120776fd3f770d1292df945a2fc4
ami
AMI_EN2001a_H03_MEE067_0210498_0210848
And that will obviously make it much easier to display
AND THAT WILL OBVIOUSLY MAKE IT MUCH EASIER TO DISPLAY
gpt-5.6-luna
MEE067
MEE067
3.5
2,104.97998
2,108.47998
AMI_EN2001a_H03_MEE067_0210498_0210848
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
12
816917763d194645a3a8266d4915f180962c962e
ami
AMI_EN2001a_H01_FEO066_0436592_0437029
Uh I ordered according to the um starting times of the utterances
UH I ORDERED ACCORDING TO THE UM STARTING TIMES OF THE UTTERANCES
gpt-5.6-luna
FEO066
FEO066
4.370117
4,365.919922
4,370.290039
AMI_EN2001a_H01_FEO066_0436592_0437029
EN2001a
H01
null
null
null
null
null
null
null
train-00000-of-00042.parquet
13
8d51f54a782999962257328809736fbcc409bbf0
ami
AMI_EN2001a_H03_MEE067_0032020_0032405
'Cause if we are I reckon we should all read our classes out of the database
'CAUSE IF WE ARE I RECKON WE SHOULD ALL READ OUR CLASSES OUT OF THE DATABASE
gpt-5.6-luna
MEE067
MEE067
3.849976
320.200012
324.049988
AMI_EN2001a_H03_MEE067_0032020_0032405
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
14
608ea72c105fd6602feebb42c2a5a54d26a79ae9
ami
AMI_EN2001a_H04_MEO069_0143300_0143643
And and probably separate to that an information about the different topics like that
AND AND PROBABLY SEPARATE TO THAT AN INFORMATION ABOUT THE DIFFERENT TOPICS LIKE THAT
gpt-5.6-luna
MEO069
MEO069
3.430054
1,433
1,436.430054
AMI_EN2001a_H04_MEO069_0143300_0143643
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
15
abbfa7fc342dc1d522ff71a39ff78c15509a6d21
ami
AMI_EN2001a_H04_MEO069_0043779_0044242
That means sort of we have multiple levels of of representation which we probably
THAT MEANS SORT OF WE HAVE MULTIPLE LEVELS OF OF REPRESENTATION WHICH WE PROBABLY
gpt-5.6-luna
MEO069
MEO069
4.630005
437.790009
442.420013
AMI_EN2001a_H04_MEO069_0043779_0044242
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
16
845a53f4be1e0811f101dfe485524e801fa11a2c
ami
AMI_EN2001a_H04_MEO069_0276847_0276933
Hmm
HMM
gpt-5.6-luna
MEO069
MEO069
0.860107
2,768.469971
2,769.330078
AMI_EN2001a_H04_MEO069_0276847_0276933
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
17
879f34508458c8a344f56393280eef18bffd2515
ami
AMI_EN2001a_H01_FEO066_0189116_0189239
Yeah
YEAH
gpt-5.6-luna
FEO066
FEO066
1.22998
1,891.160034
1,892.390015
AMI_EN2001a_H01_FEO066_0189116_0189239
EN2001a
H01
null
null
null
null
null
null
null
train-00000-of-00042.parquet
18
5f153dbf82c1af96177b8332eb1177b33061ef2a
ami
AMI_EN2001a_H04_MEO069_0044746_0044987
Then we should probably find some abstraction model
THEN WE SHOULD PROBABLY FIND SOME ABSTRACTION MODEL
gpt-5.6-luna
MEO069
MEO069
2.410004
447.459991
449.869995
AMI_EN2001a_H04_MEO069_0044746_0044987
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
19
296d4cfd4c21aaa91e139c7dfd83862f72b4ef97
ami
AMI_EN2001a_H03_MEE067_0031358_0031560
Are we still gonna dump it into a database
ARE WE STILL GONNA DUMP IT INTO A DATABASE
gpt-5.6-luna
MEE067
MEE067
2.02002
313.579987
315.600006
AMI_EN2001a_H03_MEE067_0031358_0031560
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
20
32461c68998967fd57f90aa160314acc1f4cbc2d
ami
AMI_EN2001a_H03_MEE067_0405743_0405802
Say
SAY
gpt-5.6-luna
MEE067
MEE067
0.590088
4,057.429932
4,058.02002
AMI_EN2001a_H03_MEE067_0405743_0405802
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
21
05d24295aafb69d16bfe07a4667a15e2c8486efd
ami
AMI_EN2001a_H04_MEO069_0511004_0511535
Like with the data structures I'm just like over these vague ideas of some trees I'm f
LIKE WITH THE DATA STRUCTURES I'M JUST LIKE OVER THESE VAGUE IDEAS OF SOME TREES I'M F
gpt-5.6-luna
MEO069
MEO069
5.310059
5,110.040039
5,115.350098
AMI_EN2001a_H04_MEO069_0511004_0511535
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
22
a978f4bcd995870f120a9dbbb6b621a71acd469d
ami
AMI_EN2001a_H00_MEE068_0240098_0240136
Yeah yeah
YEAH YEAH
gpt-5.6-luna
MEE068
MEE068
0.380127
2,400.97998
2,401.360107
AMI_EN2001a_H00_MEE068_0240098_0240136
EN2001a
H00
null
null
null
null
null
null
null
train-00000-of-00042.parquet
23
fbe49efa227f33417c0ff1387224a9c859f2217f
ami
AMI_EN2001a_H04_MEO069_0194411_0194948
I thought that was the whole beauty that like you can just make a new X. M. L. file and sort of tie that to the other and and it tre
I THOUGHT THAT WAS THE WHOLE BEAUTY THAT LIKE YOU CAN JUST MAKE A NEW X. M. L. FILE AND SORT OF TIE THAT TO THE OTHER AND AND IT TRE
gpt-5.6-luna
MEO069
MEO069
5.369995
1,944.109985
1,949.47998
AMI_EN2001a_H04_MEO069_0194411_0194948
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
24
b8519624187a0e2ce1b800f7d17c93b8406b0a12
ami
AMI_EN2001a_H00_MEE068_0205991_0206009
Hmm
HMM
gpt-5.6-luna
MEE068
MEE068
0.180176
2,059.909912
2,060.090088
AMI_EN2001a_H00_MEE068_0205991_0206009
EN2001a
H00
null
null
null
null
null
null
null
train-00000-of-00042.parquet
25
7fe178edcc64ba08748634a05109bbed942b797b
ami
AMI_EN2001a_H04_MEO069_0119247_0119290
Hmm
HMM
gpt-5.6-luna
MEO069
MEO069
0.430054
1,192.469971
1,192.900024
AMI_EN2001a_H04_MEO069_0119247_0119290
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
26
424b57ef19673a482467aeb32c52820b2753448d
ami
AMI_EN2001a_H00_MEE068_0132274_0132288
Mm
MM
gpt-5.6-luna
MEE068
MEE068
0.140015
1,322.73999
1,322.880005
AMI_EN2001a_H00_MEE068_0132274_0132288
EN2001a
H00
null
null
null
null
null
null
null
train-00000-of-00042.parquet
27
c58021cc5a1f60d6cf6bada6df6e563c7849fd3f
ami
AMI_EN2001a_H04_MEO069_0007991_0008261
The thing is I'm away this weekend
THE THING IS I'M AWAY THIS WEEKEND
gpt-5.6-luna
MEO069
MEO069
2.699997
79.910004
82.610001
AMI_EN2001a_H04_MEO069_0007991_0008261
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
28
ca91f1ff44a735ed7372e447a10c77737005f928
ami
AMI_EN2001a_H04_MEO069_0380400_0381446
So I'm just wondering if there's ways to abandon the whole concept of of meetings and sort of but just not really treating separate meetings as too much of a separate entity
SO I'M JUST WONDERING IF THERE'S WAYS TO ABANDON THE WHOLE CONCEPT OF OF MEETINGS AND SORT OF BUT JUST NOT REALLY TREATING SEPARATE MEETINGS AS TOO MUCH OF A SEPARATE ENTITY
gpt-5.6-luna
MEO069
MEO069
10.459961
3,804
3,814.459961
AMI_EN2001a_H04_MEO069_0380400_0381446
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
29
ee9e357e7d0ff74ccdf2eade73989d7793164e97
ami
AMI_EN2001a_H03_MEE067_0495951_0496174
So I'd just be building the data structure again
SO I'D JUST BE BUILDING THE DATA STRUCTURE AGAIN
gpt-5.6-luna
MEE067
MEE067
2.230469
4,959.509766
4,961.740234
AMI_EN2001a_H03_MEE067_0495951_0496174
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
30
9db2daac43c329db0f2ef6eff5b0cc0b10d12e64
ami
AMI_EN2001a_H04_MEO069_0342264_0342453
Yeah you'd have to count it yourself yeah
YEAH YOU'D HAVE TO COUNT IT YOURSELF YEAH
gpt-5.6-luna
MEO069
MEO069
1.890137
3,422.639893
3,424.530029
AMI_EN2001a_H04_MEO069_0342264_0342453
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
31
f651dbbf9a692295a510db90210dc157cb1e90ba
ami
AMI_EN2001a_H04_MEO069_0304005_0304468
Then skip it because it's probably something with a dot in between which is usually not something you wanna have and
THEN SKIP IT BECAUSE IT'S PROBABLY SOMETHING WITH A DOT IN BETWEEN WHICH IS USUALLY NOT SOMETHING YOU WANNA HAVE AND
gpt-5.6-luna
MEO069
MEO069
4.629883
3,040.050049
3,044.679932
AMI_EN2001a_H04_MEO069_0304005_0304468
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
32
1800e0165d61a575d331d7b80897b70e5e0cfca4
ami
AMI_EN2001a_H04_MEO069_0325487_0325565
The temps yeah
THE TEMPS YEAH
gpt-5.6-luna
MEO069
MEO069
0.779785
3,254.870117
3,255.649902
AMI_EN2001a_H04_MEO069_0325487_0325565
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
33
8411332c575c442a065089820a3cd8369adf48da
ami
AMI_EN2001a_H04_MEO069_0275384_0275512
Are they spoken numbers
ARE THEY SPOKEN NUMBERS
gpt-5.6-luna
MEO069
MEO069
1.280029
2,753.840088
2,755.120117
AMI_EN2001a_H04_MEO069_0275384_0275512
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
34
da89706e663745e5796db73c02e86bce5136088b
ami
AMI_EN2001a_H03_MEE067_0176892_0176988
Well that's easy
WELL THAT'S EASY
gpt-5.6-luna
MEE067
MEE067
0.959961
1,768.920044
1,769.880005
AMI_EN2001a_H03_MEE067_0176892_0176988
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
35
832d421efc2a589775c897b235e3fec214c5a3a2
ami
AMI_EN2001a_H01_FEO066_0474962_0475221
That's what I'm guessing that's you know
THAT'S WHAT I'M GUESSING THAT'S YOU KNOW
gpt-5.6-luna
FEO066
FEO066
2.589844
4,749.620117
4,752.209961
AMI_EN2001a_H01_FEO066_0474962_0475221
EN2001a
H01
null
null
null
null
null
null
null
train-00000-of-00042.parquet
36
d221552f752bc3dec14c8bc3802ca53fe142a1a5
ami
AMI_EN2001a_H04_MEO069_0120444_0120583
Let's check that out
LET'S CHECK THAT OUT
gpt-5.6-luna
MEO069
MEO069
1.390015
1,204.439941
1,205.829956
AMI_EN2001a_H04_MEO069_0120444_0120583
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
37
b63dfd554ec42fa985f760d150de54437170ecee
ami
AMI_EN2001a_H04_MEO069_0012177_0012665
And then just sort of everyone make sure everyone understand the interface
AND THEN JUST SORT OF EVERYONE MAKE SURE EVERYONE UNDERSTAND THE INTERFACE
gpt-5.6-luna
MEO069
MEO069
4.880005
121.769997
126.650002
AMI_EN2001a_H04_MEO069_0012177_0012665
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
38
b9405b7fec2b100906991d1477dda147d15db2f7
ami
AMI_EN2001a_H01_FEO066_0484951_0484980
Yeah
YEAH
gpt-5.6-luna
FEO066
FEO066
0.290039
4,849.509766
4,849.799805
AMI_EN2001a_H01_FEO066_0484951_0484980
EN2001a
H01
null
null
null
null
null
null
null
train-00000-of-00042.parquet
39
46d753dd98aa6158cdf5fc1cfe51bb0b53b44d98
ami
AMI_EN2001a_H03_MEE067_0097639_0097766
In memory yeah
IN MEMORY YEAH
gpt-5.6-luna
MEE067
MEE067
1.269958
976.390015
977.659973
AMI_EN2001a_H03_MEE067_0097639_0097766
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
40
583ce891e925ba510d6cf071971513314c9d381a
ami
AMI_EN2001a_H04_MEO069_0194391_0194411
Yeah
YEAH
gpt-5.6-luna
MEO069
MEO069
0.199951
1,943.910034
1,944.109985
AMI_EN2001a_H04_MEO069_0194391_0194411
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
41
a01e0a246e3b963f555706a6bb1584177bdff246
ami
AMI_EN2001a_H04_MEO069_0212730_0213069
Yeah and that's also fairly easy to store along with our segments isn't it
YEAH AND THAT'S ALSO FAIRLY EASY TO STORE ALONG WITH OUR SEGMENTS ISN'T IT
gpt-5.6-luna
MEO069
MEO069
3.389893
2,127.300049
2,130.689941
AMI_EN2001a_H04_MEO069_0212730_0213069
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
42
3e6cbcab8750336f98d1980d6462179b46d883a3
ami
AMI_EN2001a_H04_MEO069_0099586_0099696
Okay
OKAY
gpt-5.6-luna
MEO069
MEO069
1.100037
995.859985
996.960022
AMI_EN2001a_H04_MEO069_0099586_0099696
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
43
a558f8d5ba37b1579982d2428712c2e15c800793
ami
AMI_EN2001a_H01_FEO066_0441100_0441243
Yeah one group yeah
YEAH ONE GROUP YEAH
gpt-5.6-luna
FEO066
FEO066
1.430176
4,411
4,412.430176
AMI_EN2001a_H01_FEO066_0441100_0441243
EN2001a
H01
null
null
null
null
null
null
null
train-00000-of-00042.parquet
44
8d2fe0f32cf008fc3485fb00a5dd70772d2b8cfa
ami
AMI_EN2001a_H04_MEO069_0503539_0503807
When do we have to meet again then with this
WHEN DO WE HAVE TO MEET AGAIN THEN WITH THIS
gpt-5.6-luna
MEO069
MEO069
2.679688
5,035.390137
5,038.069824
AMI_EN2001a_H04_MEO069_0503539_0503807
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
45
f67d0a463ce98684a755c96360b3d9f7fc1fd899
ami
AMI_EN2001a_H03_MEE067_0309109_0309372
Yeah I it would be useful for me as well
YEAH I IT WOULD BE USEFUL FOR ME AS WELL
gpt-5.6-luna
MEE067
MEE067
2.629883
3,091.090088
3,093.719971
AMI_EN2001a_H03_MEE067_0309109_0309372
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
46
c8ba5cbc44c8d6f3ff6112106dec114615c6d723
ami
AMI_EN2001a_H04_MEO069_0000560_0000601
Gosh
GOSH
gpt-5.6-luna
MEO069
MEO069
0.41
5.6
6.01
AMI_EN2001a_H04_MEO069_0000560_0000601
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
47
d0738af837317d9d1fa76d9929bb9ecf19b57ac5
ami
AMI_EN2001a_H04_MEO069_0195726_0196470
Sort of C I was just thinking you know like if if the overhead for having the same amount of data coming from two D files instead of from one file is massive
SORT OF C I WAS JUST THINKING YOU KNOW LIKE IF IF THE OVERHEAD FOR HAVING THE SAME AMOUNT OF DATA COMING FROM TWO D FILES INSTEAD OF FROM ONE FILE IS MASSIVE
gpt-5.6-luna
MEO069
MEO069
7.439941
1,957.26001
1,964.699951
AMI_EN2001a_H04_MEO069_0195726_0196470
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
48
ac810d04256afb4752b52183c9ceca34f0f1d1f7
ami
AMI_EN2001a_H04_MEO069_0309421_0309606
Am I the only one who needs it with frequencies
AM I THE ONLY ONE WHO NEEDS IT WITH FREQUENCIES
gpt-5.6-luna
MEO069
MEO069
1.850098
3,094.209961
3,096.060059
AMI_EN2001a_H04_MEO069_0309421_0309606
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
49
c9c8e1691f96982f65045f62b6d29cba93fe9f1b
ami
AMI_EN2001a_H01_FEO066_0333857_0334962
Um I just um wondered so who's uh then doing um the frequencies on on the words
UM I JUST UM WONDERED SO WHO'S UH THEN DOING UM THE FREQUENCIES ON ON THE WORDS
gpt-5.6-luna
FEO066
FEO066
11.050049
3,338.570068
3,349.620117
AMI_EN2001a_H01_FEO066_0333857_0334962
EN2001a
H01
null
null
null
null
null
null
null
train-00000-of-00042.parquet
50
efd15d47894df6dca69b6eb97e2c86ea2008aaef
ami
AMI_EN2001a_H03_MEE067_0323471_0323505
Yeah
YEAH
gpt-5.6-luna
MEE067
MEE067
0.340088
3,234.709961
3,235.050049
AMI_EN2001a_H03_MEE067_0323471_0323505
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
51
2bf7df1e9e7b33de48e928cd034bd7190e7ea4dd
ami
AMI_EN2001a_H00_MEE068_0463820_0464033
Yeah for me it's better if they're by meeting
YEAH FOR ME IT'S BETTER IF THEY'RE BY MEETING
gpt-5.6-luna
MEE068
MEE068
2.129883
4,638.200195
4,640.330078
AMI_EN2001a_H00_MEE068_0463820_0464033
EN2001a
H00
null
null
null
null
null
null
null
train-00000-of-00042.parquet
52
38ef0c2f270893d5b4d9cbcd4846461b516d9584
ami
AMI_EN2001a_H04_MEO069_0025836_0026585
Th yeah the search is I guess the search is sort of a strange beast anyway because for the search we're leaving the nite X. M. L. framework
TH YEAH THE SEARCH IS I GUESS THE SEARCH IS SORT OF A STRANGE BEAST ANYWAY BECAUSE FOR THE SEARCH WE'RE LEAVING THE NITE X. M. L. FRAMEWORK
gpt-5.6-luna
MEO069
MEO069
7.490021
258.359985
265.850006
AMI_EN2001a_H04_MEO069_0025836_0026585
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
53
846aabd3baacf48c76c3c728f5b50d9acc8c431f
ami
AMI_EN2001a_H01_FEO066_0466281_0466707
Yeah one series has the um same three starting letters
YEAH ONE SERIES HAS THE UM SAME THREE STARTING LETTERS
gpt-5.6-luna
FEO066
FEO066
4.259766
4,662.810059
4,667.069824
AMI_EN2001a_H01_FEO066_0466281_0466707
EN2001a
H01
null
null
null
null
null
null
null
train-00000-of-00042.parquet
54
78c31d2f5db1ebae4152428622c0ac6bc842faea
ami
AMI_EN2001a_H03_MEE067_0098250_0098399
And just build one in memory
AND JUST BUILD ONE IN MEMORY
gpt-5.6-luna
MEE067
MEE067
1.48999
982.5
983.98999
AMI_EN2001a_H03_MEE067_0098250_0098399
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
55
f9c2f99680a28e65b7fdbf829a4a5411c01e843c
ami
AMI_EN2001a_H03_MEE067_0098777_0098944
I have no idea
I HAVE NO IDEA
gpt-5.6-luna
MEE067
MEE067
1.669983
987.77002
989.440002
AMI_EN2001a_H03_MEE067_0098777_0098944
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
56
793ccd352f13a0274bbc08e3a98dc872dbdb1a18
ami
AMI_EN2001a_H04_MEO069_0424718_0425031
I have that really excited pirate copied thing
I HAVE THAT REALLY EXCITED PIRATE COPIED THING
gpt-5.6-luna
MEO069
MEO069
3.129883
4,247.180176
4,250.310059
AMI_EN2001a_H04_MEO069_0424718_0425031
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
57
29bd133720af0ffc90b317e9a4550c8599398d34
ami
AMI_EN2001a_H04_MEO069_0023174_0023651
So basically apart from the display module the I the display itself
SO BASICALLY APART FROM THE DISPLAY MODULE THE I THE DISPLAY ITSELF
gpt-5.6-luna
MEO069
MEO069
4.769989
231.740005
236.509995
AMI_EN2001a_H04_MEO069_0023174_0023651
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
58
3f0b612d443a7c37ca2bfd45822e8baa288d878c
ami
AMI_EN2001a_H02_FEO065_0490168_0490205
Yeah
YEAH
gpt-5.6-luna
FEO065
FEO065
0.369629
4,901.680176
4,902.049805
AMI_EN2001a_H02_FEO065_0490168_0490205
EN2001a
H02
null
null
null
null
null
null
null
train-00000-of-00042.parquet
59
d3db2eccc0bfbbb05fe689f16f9d49b04a8972ea
ami
AMI_EN2001a_H01_FEO066_0162752_0162930
N uh no no it's F for
N UH NO NO IT'S F FOR
gpt-5.6-luna
FEO066
FEO066
1.780029
1,627.52002
1,629.300049
AMI_EN2001a_H01_FEO066_0162752_0162930
EN2001a
H01
null
null
null
null
null
null
null
train-00000-of-00042.parquet
60
2e925cf35a822aab61d1dd42c2f3cc48d1cfbcf7
ami
AMI_EN2001a_H04_MEO069_0087994_0088294
No but I mean like how how Jasmine does it internally I don't know
NO BUT I MEAN LIKE HOW HOW JASMINE DOES IT INTERNALLY I DON'T KNOW
gpt-5.6-luna
MEO069
MEO069
3
879.940002
882.940002
AMI_EN2001a_H04_MEO069_0087994_0088294
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
61
d79340c2dad8c83a266345bc7cf6b0f9beb55f40
ami
AMI_EN2001a_H01_FEO066_0433402_0433692
I can try to do it and send it to you
I CAN TRY TO DO IT AND SEND IT TO YOU
gpt-5.6-luna
FEO066
FEO066
2.899902
4,334.02002
4,336.919922
AMI_EN2001a_H01_FEO066_0433402_0433692
EN2001a
H01
null
null
null
null
null
null
null
train-00000-of-00042.parquet
62
7abd68fa0db0466658039b03facc0f922ae7e911
ami
AMI_EN2001a_H00_MEE068_0181418_0181435
Right
RIGHT
gpt-5.6-luna
MEE068
MEE068
0.169922
1,814.180054
1,814.349976
AMI_EN2001a_H00_MEE068_0181418_0181435
EN2001a
H00
null
null
null
null
null
null
null
train-00000-of-00042.parquet
63
6ad5ef151aa1d2d685ec7715a8ee56231d4c2208
ami
AMI_EN2001a_H02_FEO065_0435874_0436021
Did you also order
DID YOU ALSO ORDER
gpt-5.6-luna
FEO065
FEO065
1.469727
4,358.740234
4,360.209961
AMI_EN2001a_H02_FEO065_0435874_0436021
EN2001a
H02
null
null
null
null
null
null
null
train-00000-of-00042.parquet
64
84a2359c22a0f1e12cc495950a8050cacf5e396c
ami
AMI_EN2001a_H04_MEO069_0093349_0093712
Sort of like but that like the problem with that is it's easy to do in the text level
SORT OF LIKE BUT THAT LIKE THE PROBLEM WITH THAT IS IT'S EASY TO DO IN THE TEXT LEVEL
gpt-5.6-luna
MEO069
MEO069
3.630005
933.48999
937.119995
AMI_EN2001a_H04_MEO069_0093349_0093712
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
65
0e241b38f1b6b6d2ae5f8f92ff2c79169798354d
ami
AMI_EN2001a_H04_MEO069_0454853_0454997
Like is it just the first and the last line
LIKE IS IT JUST THE FIRST AND THE LAST LINE
gpt-5.6-luna
MEO069
MEO069
1.44043
4,548.529785
4,549.970215
AMI_EN2001a_H04_MEO069_0454853_0454997
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
66
f82b60917aeca9ce6a8f12bd1e6e9aea5789755a
ami
AMI_EN2001a_H04_MEO069_0024471_0025049
So the interface is mainly while it's running just working on data that's just loaded from a file I guess
SO THE INTERFACE IS MAINLY WHILE IT'S RUNNING JUST WORKING ON DATA THAT'S JUST LOADED FROM A FILE I GUESS
gpt-5.6-luna
MEO069
MEO069
5.779999
244.710007
250.490005
AMI_EN2001a_H04_MEO069_0024471_0025049
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
67
6a5e350ee2f5034b2578bc21251e571a6876a648
ami
AMI_EN2001a_H03_MEE067_0289725_0290180
It's just like bef until the information density is up and running
IT'S JUST LIKE BEF UNTIL THE INFORMATION DENSITY IS UP AND RUNNING
gpt-5.6-luna
MEE067
MEE067
4.550049
2,897.25
2,901.800049
AMI_EN2001a_H03_MEE067_0289725_0290180
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
68
7f41f7295d04efb8c8895b9e444ac1116fee7b04
ami
AMI_EN2001a_H03_MEE067_0405802_0406582
So then you'd start with all your utterances here and when you go up to get topic segments you go to here here here here here here here
SO THEN YOU'D START WITH ALL YOUR UTTERANCES HERE AND WHEN YOU GO UP TO GET TOPIC SEGMENTS YOU GO TO HERE HERE HERE HERE HERE HERE HERE
gpt-5.6-luna
MEE067
MEE067
7.800049
4,058.02002
4,065.820068
AMI_EN2001a_H03_MEE067_0405802_0406582
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
69
9ee093e2459f308e5b76c4cac1613c7373feaf43
ami
AMI_EN2001a_H04_MEO069_0372047_0372898
Because if we're doing like I think for for the information density we uh we should calculate it on the lowest level not on the highest
BECAUSE IF WE'RE DOING LIKE I THINK FOR FOR THE INFORMATION DENSITY WE UH WE SHOULD CALCULATE IT ON THE LOWEST LEVEL NOT ON THE HIGHEST
gpt-5.6-luna
MEO069
MEO069
8.51001
3,720.469971
3,728.97998
AMI_EN2001a_H04_MEO069_0372047_0372898
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
70
a0607f96671038a42d3248e01852d5297ba75c02
ami
AMI_EN2001a_H04_MEO069_0144018_0144100
So
SO
gpt-5.6-luna
MEO069
MEO069
0.819946
1,440.180054
1,441
AMI_EN2001a_H04_MEO069_0144018_0144100
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
71
ad58c1e44e78f4b0c7d8c4e16bf7454d74fd79de
ami
AMI_EN2001a_H04_MEO069_0141169_0141314
And they have a score
AND THEY HAVE A SCORE
gpt-5.6-luna
MEO069
MEO069
1.450073
1,411.689941
1,413.140015
AMI_EN2001a_H04_MEO069_0141169_0141314
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
72
eb30f80872cde58ca7b270ade71dd557a3e468d1
ami
AMI_EN2001a_H04_MEO069_0060512_0060622
Mm-hmm
MM-HMM
gpt-5.6-luna
MEO069
MEO069
1.099976
605.119995
606.219971
AMI_EN2001a_H04_MEO069_0060512_0060622
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
73
2e4fcac519bb62cc20ca3c4577c08d2dc13bed0d
ami
AMI_EN2001a_H02_FEO065_0271867_0272305
Yes but what are the other things that's uh some kind of number
YES BUT WHAT ARE THE OTHER THINGS THAT'S UH SOME KIND OF NUMBER
gpt-5.6-luna
FEO065
FEO065
4.380127
2,718.669922
2,723.050049
AMI_EN2001a_H02_FEO065_0271867_0272305
EN2001a
H02
null
null
null
null
null
null
null
train-00000-of-00042.parquet
74
2474cc6ac4ac59cfd305162d5512e9a1652820b0
ami
AMI_EN2001a_H01_FEO066_0064517_0065545
And that's not so much what he meant with not possibly loading everything was that you m um load all the uh annotation stuff
AND THAT'S NOT SO MUCH WHAT HE MEANT WITH NOT POSSIBLY LOADING EVERYTHING WAS THAT YOU M UM LOAD ALL THE UH ANNOTATION STUFF
gpt-5.6-luna
FEO066
FEO066
10.280029
645.169983
655.450012
AMI_EN2001a_H01_FEO066_0064517_0065545
EN2001a
H01
null
null
null
null
null
null
null
train-00000-of-00042.parquet
75
b2e24fbacc94c90ed725de968ac67ef1a244b2f9
ami
AMI_EN2001a_H03_MEE067_0070589_0070782
For every single word
FOR EVERY SINGLE WORD
gpt-5.6-luna
MEE067
MEE067
1.929993
705.890015
707.820007
AMI_EN2001a_H03_MEE067_0070589_0070782
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
76
69c080706556914f55d0fa669d300acdd21eb179
ami
AMI_EN2001a_H00_MEE068_0149028_0149049
Hmm
HMM
gpt-5.6-luna
MEE068
MEE068
0.209961
1,490.280029
1,490.48999
AMI_EN2001a_H00_MEE068_0149028_0149049
EN2001a
H00
null
null
null
null
null
null
null
train-00000-of-00042.parquet
77
fe31c68f532524bab70776b9c56d920bda158873
ami
AMI_EN2001a_H04_MEO069_0217655_0217714
Yeah
YEAH
gpt-5.6-luna
MEO069
MEO069
0.589844
2,176.550049
2,177.139893
AMI_EN2001a_H04_MEO069_0217655_0217714
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
78
5c6b74b987cd52977db844c3083ebc2baf880b12
ami
AMI_EN2001a_H04_MEO069_0372898_0372951
But like 'cause
BUT LIKE 'CAUSE
gpt-5.6-luna
MEO069
MEO069
0.530029
3,728.97998
3,729.51001
AMI_EN2001a_H04_MEO069_0372898_0372951
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
79
47d0608eb0b635e053d73e21f6a63644d31ef16f
ami
AMI_EN2001a_H01_FEO066_0188191_0188384
For example for the dialogue acts and so on
FOR EXAMPLE FOR THE DIALOGUE ACTS AND SO ON
gpt-5.6-luna
FEO066
FEO066
1.929932
1,881.910034
1,883.839966
AMI_EN2001a_H01_FEO066_0188191_0188384
EN2001a
H01
null
null
null
null
null
null
null
train-00000-of-00042.parquet
80
f8a4adf1d541888173c2198223091b0fcc7c1702
ami
AMI_EN2001a_H01_FEO066_0047482_0047500
Hmm
HMM
gpt-5.6-luna
FEO066
FEO066
0.179993
474.820007
475
AMI_EN2001a_H01_FEO066_0047482_0047500
EN2001a
H01
null
null
null
null
null
null
null
train-00000-of-00042.parquet
81
9d927a36c865c78d72fdce8576b0b434bc3e9391
ami
AMI_EN2001a_H03_MEE067_0138344_0139072
Okay so maybe we should build a B store a mean measure for the segments and meetings as well
OKAY SO MAYBE WE SHOULD BUILD A B STORE A MEAN MEASURE FOR THE SEGMENTS AND MEETINGS AS WELL
gpt-5.6-luna
MEE067
MEE067
7.280029
1,383.439941
1,390.719971
AMI_EN2001a_H03_MEE067_0138344_0139072
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
82
aa00ea283ffdd5d2d2776e4791eebca487090d75
ami
AMI_EN2001a_H04_MEO069_0139834_0140209
Then maybe we can more or less use the same code and just make a few ifs and stuff
THEN MAYBE WE CAN MORE OR LESS USE THE SAME CODE AND JUST MAKE A FEW IFS AND STUFF
gpt-5.6-luna
MEO069
MEO069
3.75
1,398.339966
1,402.089966
AMI_EN2001a_H04_MEO069_0139834_0140209
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
83
19c0f14258cb1f0a023a04869cf01d0bfd144144
ami
AMI_EN2001a_H04_MEO069_0489772_0489847
How do you do that
HOW DO YOU DO THAT
gpt-5.6-luna
MEO069
MEO069
0.75
4,897.720215
4,898.470215
AMI_EN2001a_H04_MEO069_0489772_0489847
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
84
f9c7982e3f8dbf467eb4238684c247ce197161fb
ami
AMI_EN2001a_H04_MEO069_0108365_0109244
But I'm I'm still confused 'cause I thought like that's just what Jonathan said we do C that we can't do like load a massive document of that size
BUT I'M I'M STILL CONFUSED 'CAUSE I THOUGHT LIKE THAT'S JUST WHAT JONATHAN SAID WE DO C THAT WE CAN'T DO LIKE LOAD A MASSIVE DOCUMENT OF THAT SIZE
gpt-5.6-luna
MEO069
MEO069
8.789917
1,083.650024
1,092.439941
AMI_EN2001a_H04_MEO069_0108365_0109244
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
85
838d864e8d1c9f9be0cc1570d22ae8780c5319db
ami
AMI_EN2001a_H04_MEO069_0458471_0458693
Oh then I need something different later anyway
OH THEN I NEED SOMETHING DIFFERENT LATER ANYWAY
gpt-5.6-luna
MEO069
MEO069
2.220215
4,584.709961
4,586.930176
AMI_EN2001a_H04_MEO069_0458471_0458693
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
86
82b0ea9dfd30635ba3570934b4003224c52c123f
ami
AMI_EN2001a_H04_MEO069_0353711_0353909
Yeah I I need frequency as well
YEAH I I NEED FREQUENCY AS WELL
gpt-5.6-luna
MEO069
MEO069
1.97998
3,537.110107
3,539.090088
AMI_EN2001a_H04_MEO069_0353711_0353909
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
87
32e5ca45588609a3092a6c4654a1c57000a0a421
ami
AMI_EN2001a_H04_MEO069_0310337_0310812
We can probably just start with the Java hash map and like just hash map over it and see how far we get
WE CAN PROBABLY JUST START WITH THE JAVA HASH MAP AND LIKE JUST HASH MAP OVER IT AND SEE HOW FAR WE GET
gpt-5.6-luna
MEO069
MEO069
4.75
3,103.370117
3,108.120117
AMI_EN2001a_H04_MEO069_0310337_0310812
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
88
3060d5f1c564bdce383d233c84cc86c25298a1b4
ami
AMI_EN2001a_H02_FEO065_0263972_0264145
And then yeah
AND THEN YEAH
gpt-5.6-luna
FEO065
FEO065
1.72998
2,639.719971
2,641.449951
AMI_EN2001a_H02_FEO065_0263972_0264145
EN2001a
H02
null
null
null
null
null
null
null
train-00000-of-00042.parquet
89
e11754c99af428453ea313d21ec01d938125e6e3
ami
AMI_EN2001a_H03_MEE067_0504724_0504888
Do we have to demonstrate something next week
DO WE HAVE TO DEMONSTRATE SOMETHING NEXT WEEK
gpt-5.6-luna
MEE067
MEE067
1.639648
5,047.240234
5,048.879883
AMI_EN2001a_H03_MEE067_0504724_0504888
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
90
41cde7ffd9f59fea35734dfbc0cca7b1f242873a
ami
AMI_EN2001a_H01_FEO066_0333444_0333587
Uh th yeah
UH TH YEAH
gpt-5.6-luna
FEO066
FEO066
1.430176
3,334.439941
3,335.870117
AMI_EN2001a_H01_FEO066_0333444_0333587
EN2001a
H01
null
null
null
null
null
null
null
train-00000-of-00042.parquet
91
445bfa5e7e01e7fb79dc4f7947d7c731ca991b07
ami
AMI_EN2001a_H03_MEE067_0412181_0412299
Yeah
YEAH
gpt-5.6-luna
MEE067
MEE067
1.180176
4,121.810059
4,122.990234
AMI_EN2001a_H03_MEE067_0412181_0412299
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
92
93752cdbde138a77c200c3c45f25d0165fe5dce5
ami
AMI_EN2001a_H04_MEO069_0339398_0339933
I can probably just implement like a five line Java hash table frequency dictionary builder and see
I CAN PROBABLY JUST IMPLEMENT LIKE A FIVE LINE JAVA HASH TABLE FREQUENCY DICTIONARY BUILDER AND SEE
gpt-5.6-luna
MEO069
MEO069
5.350098
3,393.97998
3,399.330078
AMI_EN2001a_H04_MEO069_0339398_0339933
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
93
f6fec5c17a6e2a5133f81fa53854373b25fb4e46
ami
AMI_EN2001a_H04_MEO069_0445600_0445650
Okay
OKAY
gpt-5.6-luna
MEO069
MEO069
0.5
4,456
4,456.5
AMI_EN2001a_H04_MEO069_0445600_0445650
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
94
d92db83113fa21f21e729adfe8b4ff9cca19bd2b
ami
AMI_EN2001a_H01_FEO066_0333826_0333857
'Kay
'KAY
gpt-5.6-luna
FEO066
FEO066
0.310059
3,338.26001
3,338.570068
AMI_EN2001a_H01_FEO066_0333826_0333857
EN2001a
H01
null
null
null
null
null
null
null
train-00000-of-00042.parquet
95
2cc5195b63c6a2a4271ba6e95813827079deae53
ami
AMI_EN2001a_H01_FEO066_0337667_0338486
So um I would for example need the um most freq um frequent words
SO UM I WOULD FOR EXAMPLE NEED THE UM MOST FREQ UM FREQUENT WORDS
gpt-5.6-luna
FEO066
FEO066
8.190186
3,376.669922
3,384.860107
AMI_EN2001a_H01_FEO066_0337667_0338486
EN2001a
H01
null
null
null
null
null
null
null
train-00000-of-00042.parquet
96
827376851ec0ca19f4f5ff8fb28c2af9688bf62e
ami
AMI_EN2001a_H03_MEE067_0232846_0232936
Like after this
LIKE AFTER THIS
gpt-5.6-luna
MEE067
MEE067
0.900146
2,328.459961
2,329.360107
AMI_EN2001a_H03_MEE067_0232846_0232936
EN2001a
H03
null
null
null
null
null
null
null
train-00000-of-00042.parquet
97
c32e748c2ea17f8e7bde88e5b7352f8ef58fd33e
ami
AMI_EN2001a_H00_MEE068_0026583_0026620
Yeah
YEAH
gpt-5.6-luna
MEE068
MEE068
0.370026
265.829987
266.200012
AMI_EN2001a_H00_MEE068_0026583_0026620
EN2001a
H00
null
null
null
null
null
null
null
train-00000-of-00042.parquet
98
1228241a46ef7cac39957e9a9ffd157eb9263a1b
ami
AMI_EN2001a_H04_MEO069_0053867_0054209
And just have different like fine grainedness levels sort of
AND JUST HAVE DIFFERENT LIKE FINE GRAINEDNESS LEVELS SORT OF
gpt-5.6-luna
MEO069
MEO069
3.420044
538.669983
542.090027
AMI_EN2001a_H04_MEO069_0053867_0054209
EN2001a
H04
null
null
null
null
null
null
null
train-00000-of-00042.parquet
99
End of preview. Expand in Data Studio

highqualASRsoup

Transcripts and metadata of an English ASR training mix built from four public corpora. No audio is included: each row carries the ids needed to fetch the audio from the upstream release.

Subset Upstream Rows Share of rows Hours Transcript
common_voice Common Voice English 26.0, train 1,147,340 30.14 % 1,812.4 as released
spgispeech SPGISpeech L, train 1,926,805 50.62 % 4,900.2 as released
gigaspeech_audiobook GigaSpeech L, audiobook-source rows 623,565 16.38 % 650.0 rewritten (see below)
ami AMI IHM, train 108,502 2.85 % 77.9 rewritten (see below)
Total 3,806,212 7,440.5

Transcript refinement

GigaSpeech and AMI ship upper-case transcripts; GigaSpeech also uses symbolic punctuation tokens (<COMMA>, <PERIOD>, ...). For those two subsets every transcript was rewritten into normal written English (casing and punctuation) by gpt-5.6-luna (prompt version 20260907-v2); the upstream transcript is kept in original_text. Common Voice and SPGISpeech transcripts are as released (original_text and text_patch_model are null), except 37 Common Voice rows whose text had been merged with the following TSV record (tab/newline in the field) during the build and was re-read literally from the release's train.tsv.

Example (gigaspeech_audiobook): SIX TOMATOES <PERIOD> → Six tomatoes.

Columns

Column Meaning
utt_id sha1 of `"
corpus subset name
id upstream utterance id: CV clip file name, SPGISpeech wav_filename, GigaSpeech segment_id, AMI audio_id
text transcript used for training (refined for GigaSpeech / AMI)
original_text, text_patch_model upstream transcript and rewrite model (GigaSpeech / AMI only)
speaker CV client_id, AMI speaker_id, GigaSpeech speaker (upstream value, usually N/A)
group leakage group for speaker/recording-disjoint splits: CV client, SPGISpeech call, GigaSpeech book (audio_id), AMI speaker
duration_seconds from metadata: SPGISpeech WAV size (16 kHz, 16-bit), CV clip_durations.tsv, GigaSpeech / AMI end_time - begin_time
begin_time, end_time segment times in the source recording (GigaSpeech, AMI)
audio_id, meeting_id, microphone_id upstream recording ids (GigaSpeech book, AMI meeting / headset; CV clip)
title, url, source, category, original_full_path GigaSpeech audiobook metadata, as released
cv_source_dataset, wav_filesize CV release tag; SPGISpeech WAV size in bytes
source_shard, source_row Parquet file and row in the soup build (SPGISpeech, GigaSpeech and AMI file names follow the upstream Hub shard names; Common Voice files are the build's own metadata shards)

Getting the audio

Join on id with the upstream release: Common Voice English 26.0 (clips/<id>), SPGISpeech (kensho/spgispeech, config L, wav_filename), GigaSpeech (speechcolab/gigaspeech, config l, segment_id), AMI (edinburghcstr/ami, config ihm, audio_id).

License

Each subset remains under its upstream license and terms of use: Common Voice (CC0-1.0), AMI (CC BY 4.0), SPGISpeech and GigaSpeech (gated on the Hub; accept their terms there). Use of these transcripts is subject to the same terms.

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