akiba resident JAV subtitlers & subtitle talk★NOT A SUB REQUEST THREAD★

maload

Active Member
Jul 1, 2008
615
117
When I see that even names aren't translated properly with auto subs ... I saw a guy who started a streaming website with uncensored FC2 vids (the ones already free everywhere) with auto subs. I had a good laugh as, as I said to him, it didn't make any sense (even very simple lines), like full random words.


Actually, there are. My service team has japanese members (even women).


today i search on the net and i found " avsubtil****** "
o great
i have been clicked on that and i watched movies .
no sub at all . its just a movie.
the worst i have seen in this business
at least he should give me something for reading when i am fapping
 

darksider59

Akiba Citizen
Feb 24, 2014
2,707
1,924
can I have ROYD-068 in SRT ver.?

I found the Chinese one in Avgle but it was already hard coded into the movie.

I tried Subtitlecat and google. But couldn't find an English translation or an SRT file.
In the topic title > ★NOT A SUB REQUEST THREAD★

today i search on the net and i found " avsubtil****** "
o great
i have been clicked on that and i watched movies .
no sub at all . its just a movie.
the worst i have seen in this business
at least he should give me something for reading when i am fapping
All their subs are auto translated in english and few other languages.
 
  • Like
Reactions: Imscully

Taako

Akiba Citizen
May 25, 2017
1,239
841
If there was a command-line utility I could feed the audio through in a filtering + conversion process I could totally implement it into my scripts. I suspect that Google's Speech-to-Text API already does filtering on their end, but it wouldn't hurt giving it a try and do an A-B test to see if passing the audio through some program yielded better results.
Wouldn't some movies with loud music stop this process?

I swear whoever edits some of these movies need to know basic post production 101:mad: The music should NEVER be louder than the dialog.
 

ssjgoku4

Member
Jan 20, 2021
27
40
I'm a software engineer with nearly a decade of experience. Today I figured out how to use Google Cloud Compute to transcribe and translate JAVs pretty reliably using some engineer's open source project on GitHub I found.

Rough estimates but...
From start to finish it takes me about 90 seconds of manual manipulation and perhaps 10 minutes of waiting to generate an SRT file.

If I batch translate multiple at once I can done one after the other after the other.

I'm still on Google Compute Cloud's free trial lasting 90 days and offering $300 of credit, but by my rough estimate it costs maybe $0.10-0.25 USD in API costs to translate a 2 hour video. Totally pulling that number out of my ass but the point is it's cheap.

Hope to record and show a demo of this soon. I know I have like zero presence on this Forum but I've had this account for a long time and built most of my JAV collection here. So... feel like sharing in some of the amazing good fortune.

Update 1 - 2022-09-10
It's late and I got way too into this tool. I translated about 70-80 hours or so of JAV material and it cost me about $21.80 in credits. That averages about $0.30 USD an hour. So, my estimate was off, but it's still pretty cheap. Again, I've got $300 of complimentary credit. So whatever.

I might not be able to record a demo of the thing working for a couple of days (I realize I'm going to need to do some editing to hide persona details from a screen recording I hope to make). I have a day job. But I hope to share some updates on how I might translate for people with cool JAVs. I'll give details, but with a free tool on PC/MacOS/Linux anyone should be able to get me the material to perform a translation with a simple share of an audio-only mkv that takes mere moments to create and will only be a like 100mb to send to me.

I'll figure out a method to share the SRTs I've created thus far.

Update 2 - 2022-09-10
These are all entirely random. And most of them are probably closer to a decade old than not. What can I say? I don't download JAVs as often as I used to and I'm pretty content with the library I built in my early 20s. Lots of incest and kinky stuff.

If someone viewing this happens to potentially have one of these videos, give it a try!

Even if you don't download a copy anyway.

For any engineers out there. Have at it: TreeAntSan/trans_video_subs: Auto Translate and add subtitle to video on Google Cloud (github.com)

This is seriously advanced stuff. So... uhhh... not going to trouble shoot your issues, so don't even ask. Wait until I reply again.

Update 3 - 2022-09-10
Haha, holy shit. Never mind about the price prediction. My credit count got updated. It's looking like I'm getting charged about a $1 USD an hour. Still cheap. But this evening of rallying through a bunch of JAVs cost $80 USD. Hoo boy. Still pretty worth it.

Gotta say, top of all. Only going to get fun results with JAVs with roleplay or story. There needs to be a lot of talking. Otherwise you're liable to pay good money for just "Ohh it's so big" or "don't stop"... which isn't fun.

Update 4 - 2022-09-11
More SRT files shared. Now 39 in total (7 more than yesterday).

I've added a slew of bash scripts (scripts you can use in Linux and MacOS) that remove most of the repetitive tasks that'd otherwise require manipulation with MKVToolNix GUI.

Update 5 - 2022-09-11
Oh, and I also discovered a way to cut my Speech-to-Text API costs (the greatest source of cost) down by about 66%. If you let Google perform analysis on your uploaded audio they give you a 33% discount. And they also charge per channel. So a stereo audio track doubles the cost. So, I obviously adjusted the tools to mix down all audio to mono. That's makes the API 66.67% cheaper to use.

From $0.012 USD per 15 seconds to $0.004 USD per 15 seconds. That's equivalent to dropping a 2hr JAV from costing $5.76 USD ((2*60*60/15) * 0.012) to $1.92 USD ((2*60*60/15) * 0.004).

I'll have to trust the price drop will come, I'm only fairly certain I've dropped the price 66%.

Next comes translation. While each transcript's length varies, I imagine we can expect anywhere from 7,000 to 15,000 characters to be used per video (this is a big guess-timate, I don't currently have any samples of actual counts, really just doing word-counts of English after-the-fact).

Translate API costs come to $20 USD per 1,000,000 characters translated (incoming). It helps that Japanese consumes fewer characters than English. So if a video had 10,000 Japanese characters that'd be a pretty humble $0.20 USD.

So, a two hour video would probably cost $2.12 USD or so to complete. I checked the cost of the Cloud Run instance and it's really quite small. In generating 39 videos' worth of translations, the cost of the computing has only come to $5.69 USD so far, which is tiny.
I created my own method too using mozilla deepspeech, i collected all the Japanese speech database i could find to train the AI and after many test and trails i got astonishing result. But due to the complication of using it i didn't share it here as it will go over the head of average users. I am working on making a user friendly version will release if it gets completed.
 

maload

Active Member
Jul 1, 2008
615
117
I created my own method too using mozilla deepspeech, i collected all the Japanese speech database i could find to train the AI and after many test and trails i got astonishing result. But due to the complication of using it i didn't share it here as it will go over the head of average users. I am working on making a user friendly version will release if it gets completed.
I created my own method too using mozilla deepspeech, i collected all the Japanese speech database i could find to train the AI and after many test and trails i got astonishing result. But due to the complication of using it i didn't share it here as it will go over the head of average users. I am working on making a user friendly version will release if it gets completed
i think you talk about you create japanese model ?
can you share your japanese pretrained model


 
  • Like
Reactions: mei2

tangerinefeline

New Member
Sep 22, 2022
3
8
So OpenAI just released Whisper, their speech to text AI, and the transcription seems pretty decent from what I tested using Google Colab.

Screenshot 2022-09-22 17.34.33.png

It's also relatively simple since it's only one command to do a Japanese -> English transcription.

Here's the Github repo for it: https://github.com/openai/whisper

Here's the Colab notebook for it, just replace the file_location variable with a link to the audio file you want to transcribe: https://colab.research.google.com/drive/1j3-_EF43nUCeIkrzpk_jpamtFZmURYrU?usp=sharing
 

maload

Active Member
Jul 1, 2008
615
117
So OpenAI just released Whisper, their speech to text AI, and the transcription seems pretty decent from what I tested using Google Colab.

View attachment 3045996

It's also relatively simple since it's only one command to do a Japanese -> English transcription.

Here's the Github repo for it: https://github.com/openai/whisper

Here's the Colab notebook for it, just replace the file_location variable with a link to the audio file you want to transcribe: https://colab.research.google.com/drive/1j3-_EF43nUCeIkrzpk_jpamtFZmURYrU?usp=sharing
thank you so much , i want to test it .
 
  • Like
Reactions: tangerinefeline

Taako

Akiba Citizen
May 25, 2017
1,239
841
So OpenAI just released Whisper, their speech to text AI, and the transcription seems pretty decent from what I tested using Google Colab.

View attachment 3045996

It's also relatively simple since it's only one command to do a Japanese -> English transcription.

Here's the Github repo for it: https://github.com/openai/whisper

Here's the Colab notebook for it, just replace the file_location variable with a link to the audio file you want to transcribe: https://colab.research.google.com/drive/1j3-_EF43nUCeIkrzpk_jpamtFZmURYrU?usp=sharing
Thank you for sharing.
Have you tested during scenes that are low speaking, multiple people talking, and background noises such as music and etc?
Those are the common complaints and should be the real test.
 

tangerinefeline

New Member
Sep 22, 2022
3
8
Thank you for sharing.
Have you tested during scenes that are low speaking, multiple people talking, and background noises such as music and etc?
Those are the common complaints and should be the real test.

Hmm not yet, to be honest I usually only lurk here, is there a human made translation that would be good to do a comparison to? I think this is useful when you have videos that might be a little bit older or obscure which are difficult to find subtitles for, and definitely not a replacement yet for human transcription.
 
  • Like
Reactions: Taako

Taako

Akiba Citizen
May 25, 2017
1,239
841
Hmm not yet, to be honest I usually only lurk here, is there a human made translation that would be good to do a comparison to? I think this is useful when you have videos that might be a little bit older or obscure which are difficult to find subtitles for, and definitely not a replacement yet for human transcription.
I appreciate your honest answer.
I'm not surprise you mention older jav. I regularly subbed older jav because no one really created subs for them and I think the movies are better acted and have more convincing sex scenes. :D

Also many old jav don't have the loud background music and multiple people talking. It's good for subbing.

It seem all the models work generously given clear speaking and less background noise. I'll be impress when a translation software can do that and be affordable. I'm sure many govt security, police forces, military, and movie studios have and uses the tech.
 

mei2

Well-Known Member
Dec 6, 2018
217
354
So OpenAI just released Whisper, their speech to text AI, and the transcription seems pretty decent from what I tested using Google Colab.

View attachment 3045996

It's also relatively simple since it's only one command to do a Japanese -> English transcription.

Here's the Github repo for it: https://github.com/openai/whisper

Here's the Colab notebook for it, just replace the file_location variable with a link to the audio file you want to transcribe: https://colab.research.google.com/drive/1j3-_EF43nUCeIkrzpk_jpamtFZmURYrU?usp=sharing

@tangerinefeline , thanks for this. New tools and methods are always welcome!

The technology (and the research paper) look quite promising. So I quickly ran few tests on it --thanks for the link to the colab. Makes things so much faster. Beside, the large models need like 16GB VRAM :).

I ran Whisper on 2 new files released today: SSIS-525 Aoi Tsukasa, And JUQ-098 Nao Jinguuji. I ran default model w translation, default model, large model, and medium. FWIW, here is what I observed so far:

- Overal: it is quite promising but it seems that at least the Japanese model needs more training and calibration.
- Ease of use: Good! The colab especially makes it very easy to use.
- Dialogue detection: Not very good.
- Timing: Not good. Transcription is all over the place. I have a feeling that this is caused by Huggingface transformers.
- Translation: I suggest not to use it. The one version that I looked at seemed to be off.
- Comparison with VOX: the vox version through subtitleedit produces much more accurate dialogue timing. But the dialogue detection seem to be in par with Whisper.


I'm keen to hear from @ssjgoku4 about his retrained model. We seem to have some quite tech-smart people in this forum. It would be great if we put our efforts together to work on training (a selected) model for JAV. May be we can setup a Patreaon perhaps ?
 

Attachments

  • JUQ-098.ja Nao Jinguuji - WHISPER MEDIUM.zip
    18 KB · Views: 137
  • SSIS-525.ja Aoi Tsukasa - WHISPER LARGE.zip
    1 KB · Views: 139

SUNBO

Active Member
Nov 19, 2007
115
77
can I have ROYD-068 in SRT ver.?

I found the Chinese one in Avgle but it was already hard coded into the movie.

I tried Subtitlecat and google. But couldn't find an English translation or an SRT file.
If you are desperate you can use your phone's app "google translate" and use the camera option. But the problem with this is.... you need a third hand. One hand to hold the phone, one hand to skip forward, and one hand to touch your little brother.
 

SUNBO

Active Member
Nov 19, 2007
115
77
@tangerinefeline , thanks for this. New tools and methods are always welcome!

The technology (and the research paper) look quite promising. So I quickly ran few tests on it --thanks for the link to the colab. Makes things so much faster. Beside, the large models need like 16GB VRAM :).

I ran Whisper on 2 new files released today: SSIS-525 Aoi Tsukasa, And JUQ-098 Nao Jinguuji. I ran default model w translation, default model, large model, and medium. FWIW, here is what I observed so far:

- Overal: it is quite promising but it seems that at least the Japanese model needs more training and calibration.
- Ease of use: Good! The colab especially makes it very easy to use.
- Dialogue detection: Not very good.
- Timing: Not good. Transcription is all over the place. I have a feeling that this is caused by Huggingface transformers.
- Translation: I suggest not to use it. The one version that I looked at seemed to be off.
- Comparison with VOX: the vox version through subtitleedit produces much more accurate dialogue timing. But the dialogue detection seem to be in par with Whisper.


I'm keen to hear from @ssjgoku4 about his retrained model. We seem to have some quite tech-smart people in this forum. It would be great if we put our efforts together to work on training (a selected) model for JAV. May be we can setup a Patreaon perhaps ?
Hey thanks for mentioning that SubtitleEdit can transcribe audio! It seems to be available only from March 2022 this year. I just tested it on one of my favourite JAV (KTFT-004) and had great results. 95% of it were transcribed, 70% were translated accurately (meaning it made sense). Which was a huge improvement from pyTranscriber which I had issues with, only about 30-50% transcribed due to it using google speech recognition API and google API is bad at detecting voice that's a bit distant from camera.
 
  • Like
Reactions: mei2

Taako

Akiba Citizen
May 25, 2017
1,239
841
@tangerinefeline , thanks for this. New tools and methods are always welcome!

The technology (and the research paper) look quite promising. So I quickly ran few tests on it --thanks for the link to the colab. Makes things so much faster. Beside, the large models need like 16GB VRAM :).

I ran Whisper on 2 new files released today: SSIS-525 Aoi Tsukasa, And JUQ-098 Nao Jinguuji. I ran default model w translation, default model, large model, and medium. FWIW, here is what I observed so far:

- Overal: it is quite promising but it seems that at least the Japanese model needs more training and calibration.
- Ease of use: Good! The colab especially makes it very easy to use.
- Dialogue detection: Not very good.
- Timing: Not good. Transcription is all over the place. I have a feeling that this is caused by Huggingface transformers.
- Translation: I suggest not to use it. The one version that I looked at seemed to be off.
- Comparison with VOX: the vox version through subtitleedit produces much more accurate dialogue timing. But the dialogue detection seem to be in par with Whisper.


I'm keen to hear from @ssjgoku4 about his retrained model. We seem to have some quite tech-smart people in this forum. It would be great if we put our efforts together to work on training (a selected) model for JAV. May be we can setup a Patreaon perhaps ?
Thank you both for testing this new tech and capabilities.

Thank you, @mei for running tests and giving us the data and your experience using this new model that @tangerinefeline was graciously told us all about. :D

And @mei, i for one appreciate you taking the time to check out this new translation and giving us a through analyst and your thoughts on it.

It's classy acts like this is why I really like AKIBA Online, the people and the moderators are just so much down to earth, fun, and professional:cheers:
 

mei2

Well-Known Member
Dec 6, 2018
217
354
Hey thanks for mentioning that SubtitleEdit can transcribe audio! It seems to be available only from March 2022 this year. I just tested it on one of my favourite JAV (KTFT-004) and had great results. 95% of it were transcribed, 70% were translated accurately (meaning it made sense). Which was a huge improvement from pyTranscriber which I had issues with, only about 30-50% transcribed due to it using google speech recognition API and google API is bad at detecting voice that's a bit distant from camera.

If you haven't done it yet, download the Vosk Japanese Large model --it produces better results for me than the default Japanese Small model.
 
Last edited:

javjod

Member
Feb 5, 2021
26
37
another method, using CapCut app on android phone choose : Text --> Auto Captions --> Select language --> Japanese --> Start
 

avatarthe

Well-Known Member
Feb 1, 2008
184
277
thanks for the tip, i'll do that now. I used the small model because it says the large model is for servers.


poster.jpg

I decided to test VOSK vs Pytranscriber on the opening of MIAA-698 -[Single Mom Reserve Army] The Hurdles To SEX Are Too Low, Can't Stand My Sweaty Eldest Daughter Naked Every Day! Lima Arai (2022) as the opening is a simple monologue from the father with no music... plus Lima Arai is Sooo hot in this film as the daughter with hyperhydrosis (Over active sweat gland) who is always so hot and sweaty that she never wear cloths (well she wears sock and the tie for her school uniform) that it real deserves subtitles.

I think Pytransriber did a bettre job, what has other peoples experience bee?



Pytranscriber
Vosk Japanese Large model​
1
00:00:00,256 --> 00:00:06,400
Hello. I'm surprised to see an old man out of nowhere.











2
00:00:06,656 --> 00:00:12,800
Please take a few minutes of your time.
















3
00:00:13,056 --> 00:00:19,200
This time, I'd like to share with you a little bit about myself.















4
00:00:19,456 --> 00:00:25,600
I'd like to share with you my story.






















5
00:00:25,856 --> 00:00:32,000
I'm sorry I'm late to introduce myself.

6
00:00:32,256 --> 00:00:38,400
I'm a little rough around the edges, but I'm the mainstay of my family. I'm right after my father.




















7
00:00:38,656 --> 00:00:44,800
As you can see, I'm not a magazine model.

















8
00:00:45,056 --> 00:00:51,200
I'm a regular office worker. There's no Araike here.
















9
00:00:51,456 --> 00:00:57,600
Because eight years ago, my wife left me for a young man she worked with part-time.





































10
00:00:57,856 --> 00:01:04,000
She got tired of him and left him.



















11
00:01:04,256 --> 00:01:05,536
Since then, I've been the mainstay of Araike for three years.

12
00:01:05,792 --> 00:01:11,680
I've been the mainstay of Araike's household, raising our three children.

13
00:01:11,936 --> 00:01:14,496
Now then...

































14
00:01:15,008 --> 00:01:17,824
I would like to introduce you to my lovely children.

15
00:01:18,336 --> 00:01:24,480
First of all, my son, my eldest, is my favorite, a college student.

16
00:01:24,736 --> 00:01:30,880
He is a serious boy, and I guess he is more solid than I am.

17
00:01:31,136 --> 00:01:33,184
Lately, he's been...

18
00:01:33,440 --> 00:01:35,232
Muscle training, Yamanote...

19
00:01:35,744 --> 00:01:37,536
A typhoon is coming.

20
00:01:37,792 --> 00:01:43,936
Maybe he's got too much power.




















































21
00:01:44,960 --> 00:01:51,104
Next is Shinji, my second and youngest son.

22
00:01:53,920 --> 00:02:00,064
He doesn't go to school.

23
00:02:00,320 --> 00:02:06,464
Animated? He's always doing that.

24
00:02:06,720 --> 00:02:12,864
A recluse. Me too.

25
00:02:13,120 --> 00:02:17,472
I don't get to see him much.

26
00:02:17,728 --> 00:02:19,520
I don't get to see him much, so I don't know what he's thinking.

27
00:02:19,776 --> 00:02:24,640
I don't know what he's thinking.















































































28
00:02:25,152 --> 00:02:31,296
I'm Rima, the eldest between two sons.

29
00:02:31,552 --> 00:02:37,696
She's the problem child of Araike.

30
00:02:37,952 --> 00:02:44,096
She never wears clothes and spends most of her time at home completely naked.

31
00:02:44,352 --> 00:02:50,496
She can't even study... and she's not in school.

32
00:02:54,592 --> 00:03:00,736
She's a gal? Also, for some reason, she's always sweaty since she was a kid.

33
00:03:02,528 --> 00:03:05,344
Is she expensive?

34
00:03:05,856 --> 00:03:12,000
This time, Lima is causing all kinds of trouble.

35
00:03:12,256 --> 00:03:18,400
Let's see... naked and covered in sweat with my eldest daughter.














































































































































































































































1
00:00:01,200 --> 00:00:02,400
Hi there.

2
00:00:04,110 --> 00:00:05,520
I'm sure some of you are surprised to see your uncle out of nowhere.

3
00:00:06,180 --> 00:00:08,088
I know some of you were surprised.

4
00:00:09,180 --> 00:00:10,180
It's just for a few hours.

5
00:00:10,680 --> 00:00:11,680
Please bear with me.

6
00:00:13,410 --> 00:00:14,410
This time

7
00:00:14,614 --> 00:00:15,614
I'd like to send you

8
00:00:18,090 --> 00:00:19,680
I don't know if I should say this myself, but...

9
00:00:20,401 --> 00:00:21,401
I'm a little...

10
00:00:23,250 --> 00:00:24,270
I've changed a lot.

11
00:00:25,470 --> 00:00:26,470
My family

12
00:00:27,090 --> 00:00:28,620
It's a story about a coarse house.

13
00:00:30,660 --> 00:00:31,950
I'm late to introduce myself.

14
00:00:33,090 --> 00:00:34,090
I am

15
00:00:34,140 --> 00:00:35,504
The mainstay of our coarse family.

16
00:00:36,240 --> 00:00:37,800
I'm Taku, my father.

17
00:00:38,910 --> 00:00:40,110
As you can see...

18
00:00:40,560 --> 00:00:41,730
I'm not a magazine model

19
00:00:42,270 --> 00:00:43,270
I'm not

20
00:00:45,360 --> 00:00:46,830
I'm just an ordinary office worker

21
00:00:46,830 --> 00:00:47,830
I'm an ordinary businessman.

22
00:00:48,840 --> 00:00:49,840
Washing machine

23
00:00:50,268 --> 00:00:51,268
I don't have a washing machine

24
00:00:52,321 --> 00:00:53,321
I'm not a washer.

25
00:00:53,970 --> 00:00:54,180
8 years ago

26
00:00:54,210 --> 00:00:55,290
years ago, my wife

27
00:00:55,800 --> 00:00:56,070
part time job

28
00:00:56,070 --> 00:00:58,193
I've been working with a lot of young men.

29
00:00:59,670 --> 00:01:00,300
She got tired of me.

30
00:01:00,661 --> 00:01:01,661
She got tired of me.

31
00:01:01,860 --> 00:01:02,860
She left me.

32
00:01:04,140 --> 00:01:05,250
And then I went back to

33
00:01:06,030 --> 00:01:06,750
As the mainstay

34
00:01:06,990 --> 00:01:08,100
As the mainstay

35
00:01:09,120 --> 00:01:09,210
Three...

36
00:01:09,229 --> 00:01:10,229
I've raised three children.

37
00:01:10,410 --> 00:01:11,410
I've raised three children.

38
00:01:13,530 --> 00:01:14,530
And now...

39
00:01:15,000 --> 00:01:17,730
I would like to introduce you to my lovely children.

40
00:01:18,570 --> 00:01:19,920
Let's start from there.

41
00:01:21,630 --> 00:01:22,830
My eldest son Daisuke.

42
00:01:23,340 --> 00:01:24,340
He's a college student, isn't he?

43
00:01:26,100 --> 00:01:27,630
He's very serious.

44
00:01:28,650 --> 00:01:31,200
I guess he's more solid than I am.

45
00:01:31,950 --> 00:01:33,060
What is he doing these days?

46
00:01:33,870 --> 00:01:34,348
muscle training

47
00:01:34,348 --> 00:01:35,348
She's into muscle training.

48
00:01:35,730 --> 00:01:37,440
She seems to be working out a lot.

49
00:01:38,220 --> 00:01:38,591
Maybe he has too much power

50
00:01:38,591 --> 00:01:39,990
Maybe he has too much power.

51
00:01:43,444 --> 00:01:44,640
It might be amazing.

52
00:01:47,370 --> 00:01:48,370
Next...

53
00:01:49,230 --> 00:01:50,230
Second son

54
00:01:50,640 --> 00:01:50,910
Check

55
00:01:50,910 --> 00:01:51,000
of

56
00:01:51,327 --> 00:01:52,327
Check it out!

57
00:01:53,880 --> 00:01:54,960
This boy

58
00:01:56,520 --> 00:01:57,870
He doesn't go to school.

59
00:02:02,400 --> 00:02:03,400
Anime

60
00:02:03,750 --> 00:02:03,990
Mecha

61
00:02:04,230 --> 00:02:04,500
or...

62
00:02:05,130 --> 00:02:06,540
That's all she does.

63
00:02:09,085 --> 00:02:10,085
That's nice.

64
00:02:11,550 --> 00:02:12,550
Me too.

65
00:02:13,230 --> 00:02:15,420
I don't know what he's thinking.

66
00:02:17,790 --> 00:02:19,530
I don't know what he's thinking.

67
00:02:20,220 --> 00:02:21,420
I don't know what he's thinking.

68
00:02:23,880 --> 00:02:24,880
Finally.

69
00:02:25,800 --> 00:02:26,800
The first son

70
00:02:27,180 --> 00:02:28,180
The second son

71
00:02:28,890 --> 00:02:29,890
The eldest daughter.

72
00:02:29,945 --> 00:02:30,945
Now.

73
00:02:32,790 --> 00:02:34,020
This is Koga.

74
00:02:34,650 --> 00:02:36,210
She's the problem child of the family.

75
00:02:36,990 --> 00:02:37,990
First of all...

76
00:02:38,220 --> 00:02:38,640
Clothes.

77
00:02:38,790 --> 00:02:39,790
No clothes.

78
00:02:39,960 --> 00:02:42,480
She spends most of her time at home completely naked.

79
00:02:44,400 --> 00:02:45,400
Also...

80
00:02:45,810 --> 00:02:46,810
I don't know how to say it.

81
00:02:47,430 --> 00:02:48,690
I can't even study.

82
00:02:49,500 --> 00:02:51,390
I didn't finish school.

83
00:02:53,283 --> 00:02:54,283
I'm what's called

84
00:02:54,660 --> 00:02:54,960
Gyaru

85
00:02:54,960 --> 00:02:55,960
I guess you could say

86
00:02:56,790 --> 00:02:57,840
I don't know why.

87
00:02:58,710 --> 00:03:01,200
I've come all this way since I was a kid.

88
00:03:02,550 --> 00:03:04,290
I wonder if she has hyperhidrosis.

89
00:03:06,120 --> 00:03:07,120
This time

90
00:03:07,530 --> 00:03:07,830
This

91
00:03:08,040 --> 00:03:09,040
is

92
00:03:10,800 --> 00:03:12,030
It's going to be a problem.

93
00:03:14,010 --> 00:03:15,207
Well then...

94
00:03:15,750 --> 00:03:16,890
Naked eldest daughter and

95
00:03:18,089 --> 00:03:19,089
covered in
 

Attachments

  • folder.jpg
    folder.jpg
    41.9 KB · Views: 62
  • poster.jpg
    poster.jpg
    41.9 KB · Views: 55
  • Like
Reactions: Taako and mei2

Taako

Akiba Citizen
May 25, 2017
1,239
841
I agree with @avatarthe. Pytranscriber still delivers good results.
I use it mostly for timing but when it translate things correctly than it's a bonus :D

The sub I'm using for example was tweak by me with Aegisub and Pytranscriber and SubtitleEdit. I have fallen in love with Aeigusb as I used that as my final clean up. IMSCULLY and some of my reddit friends have really shown me the power of it.

As you might guess, this sub is 90% finish but I haven't released it yet.
ZUKO-098.jpg
 

Attachments

  • ZUKO-098.rar
    3.7 KB · Views: 105
  • Like
Reactions: mei2

SUNBO

Active Member
Nov 19, 2007
115
77
I decided to test VOSK vs Pytranscriber on the opening of MIAA-698 -[Single Mom Reserve Army] The Hurdles To SEX Are Too Low, Can't Stand My Sweaty Eldest Daughter Naked Every Day! Lima Arai (2022) as the opening is a simple monologue from the father with no music... plus Lima Arai is Sooo hot in this film as the daughter with hyperhydrosis (Over active sweat gland) who is always so hot and sweaty that she never wear cloths (well she wears sock and the tie for her school uniform) that it real deserves subtitles.

I think Pytransriber did a bettre job, what has other peoples experience bee?
I watched the intro with both subtitles. I could see the difference. VOSK breaks up sentences, but detects more words (not as obvious with this video but others). PyTranscriber have longer sentences. When both are machine translated, its a close tie. Some words were translated better with VOSK, some better with pytranscriber. (For example, pytranscriber translated the second son's name as Shinji, Vosk did not catch it. Vosk translated "anime" "mecha" for second son's interest, but pyTranscriber translated "animated?". Pytranscriber translated about his wife left him for young man 8 years ago, Vosk did not translate that part properly. Vosk said something about washing machines, but Pytranscriber completely missed that. Pytranscriber missed out "I'm Taku, the father") I still prefer VOSK though, mainly because it doesn't miss out on words, and ease of use.

Also I have an issue with pytranscriber not sure if any of you have it. When I transcribe anything longer than 15min or so, it will get timed out between 40%-85%, and get stuck there. I had to split the video in order to transcribe.
 
  • Like
Reactions: mei2