Post your JAV subtitle files here - JAV Subtitle Repository (JSP)★NOT A SUB REQUEST THREAD★
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[Reducing Mosaic]JUR-003 A Two-day, One-night Trip To Milk My Aunt Who Has Sex With Her Husband Every Night. I Was A Virgin Who Woke Up To Sex After Being Fucked So Many Times… I Forgot Everything And Got Addicted To Continuous Cream-pie Sex. Yumi Kazama
I downloaded and Subbed this recent, reduced mosaic Aunt-Nephew Incest themed movie starring one of my favorite MILFs. I used Whisper Colab to create this Sub and I also attempted to clean it up a bit and re-interpreted some of the meaningless/ "lewd-less" dialog. Again, I don't understand Japanese so my re-interpretations might not be totally accurate but I try to match what's happening in the scene. Anyway, enjoy and let me know what you think.
Easy way on windows, right-click the file, go to the "send to" menu and select "compressed (zipped) folder".
If you are using a Windows System, bring up the JAV Movie sub-directory, right click on the JAV Movie.srt file and then click on Add to "JAV Movie.rar" and file explorer will create a Jav Moie.rar file in the same directory which can be attached to your post. Pretty easy really!
That only works if you have winrar installed. Similar archival software will have similar options too, but unlikely they have those if they don't know how to use them.
MESS-023 - A Mother and Daughter Taken by Another Woman - Maya Sawamura, Ayaka Mizuki and Erika Hiramatsu
English subtitles done the best I could, starting off. If anyone can complete it to a 100% accurate English subtitles. I'd be most grateful.
English subtitles done the best I could, starting off. If anyone can complete it to a 100% accurate English subtitles. I'd be most grateful.
100% accurate English subtitles? That probably leaves most of us out!
100% accurate subtitles?
About as likely as finding 100% honest women.
Or strippers who are only doing it to put themselves through college.
Reminds me of that old joke:
Do you know the difference between an honest woman and Bigfoot?
Ans: There have been reported sightings of Bigfoot!
[Reducing Mosaic]FERA-114 If I Let My Mother Drink An Aphrodisiac …When I Tried To Give My Mother A Rumored Drug That I Got From My Class Friends, I Was Attacked By Yuka Mizuno
I downloaded this recent, reduced mosaic Mother-Son Incest themed JAV. I used Whisper Colab to create this Sub but I had started editing a Sub that I had downloaded from SubtitleCat a couple of years ago but never finished. I used the Whisper version as the base and used the downloaded sub to fill in and provide clarification in several places. I also attempted to clean it up a bit and re-interpreted some of the meaningless/ "lewd-less" dialog. Again, I don't understand Japanese so my re-interpretations might not be totally accurate but I try to match what's happening in the scene. Anyway, enjoy and let me know what you think.
Saw the preview trailer of this and its definitely hot! Yumi's nephew is all over her like an energizer bunny! Thanks Chuckie![Reducing Mosaic]JUR-003 A Two-day, One-night Trip To Milk My Aunt Who Has Sex With Her Husband Every Night. I Was A Virgin Who Woke Up To Sex After Being Fucked So Many Times… I Forgot Everything And Got Addicted To Continuous Cream-pie Sex. Yumi Kazama
I downloaded and Subbed this recent, reduced mosaic Aunt-Nephew Incest themed movie starring one of my favorite MILFs. I used Whisper Colab to create this Sub and I also attempted to clean it up a bit and re-interpreted some of the meaningless/ "lewd-less" dialog. Again, I don't understand Japanese so my re-interpretations might not be totally accurate but I try to match what's happening in the scene. Anyway, enjoy and let me know what you think.
Madonna is out with some great new titles this holiday month including one of my favorite MILFs Ririko Kinoshita in her own "married woman dancing at a strip theater" which is my favorite Madonna series going back to the days of the original 3 moms stripping- Misa Yuki, Yumi Kazama and Sakiko Mihara.
Could you help me with the error message I get?
NameError Traceback (most recent call last)
<ipython-input-6-1bc508f8c32b> in <cell line: 37>()
35 out_path = os.path.splitext(audio_path)[0] + ".srt"
36 out_path_pre = os.path.splitext(audio_path)[0] + "_Untranslated.srt"
---> 37 if source_separation:
38 print("Separating vocals...")
39 get_ipython().system('ffprobe -i "{audio_path}" -show_entries format=duration -v quiet -of csv="p=0" > input_length')
NameError: name 'source_separation' is not defined
The help in Whisper doesn't seem to make it clear what it is I'm supposed to do.
I have tried to just check the box at Source Separation but that doesn't do it.
Thanks.
I've ran into the same issue. For some reason(not sure how that works on the colab), the variables defined in the first block aren't seen by the last script so I just copied the whole code from the first block and put it at the start(make sure you add some empty line to where you paste) of the last so it can see them. Just make sure to do the changes you want done first before the copy pasting or wait for someone who understand how it works to tell you how to properly use it.
Thanks, SamKook. No, I don't know anything about code or scripts, really. I never used source separation on the old Colab because it never worked.
I'll see if I can use this. In the meantime I'll use the old Colab and Faster Whisper using the model Medium. The large model gives me SO many bad lines. I wonder why.
I'll see if I can use this. In the meantime I'll use the old Colab and Faster Whisper using the model Medium. The large model gives me SO many bad lines. I wonder why.
There's 3 version of large.
From my limited testing, I've found that v3 seems to more aggressively try to detect speech so it finds more but also makes a lot of mistakes and v2 finds less but also makes less mistakes.
Not too sure about v1, didn't notice anything particular about it. I've found comparing to be mostly useless since even comparing the exact same settings with the exact same model can give wildly different results so seems more like luck than anything else for what you get with some general tendencies.
From my limited testing, I've found that v3 seems to more aggressively try to detect speech so it finds more but also makes a lot of mistakes and v2 finds less but also makes less mistakes.
Not too sure about v1, didn't notice anything particular about it. I've found comparing to be mostly useless since even comparing the exact same settings with the exact same model can give wildly different results so seems more like luck than anything else for what you get with some general tendencies.
Are there parameters in Faster Whisper for using different versions? I didn't look that hard for command line parameters for Faster Whisper but what I found was just small, medium and large.
This is what I use:
faster-whisper-xxl.exe File.mp4 --language ja --task transcribe --model large --compute_type auto --device cuda --standard --print_progress --vad_alt_method pyannote_v3 --vad_min_silence_duration_ms 2000
The version model in Faster Whisper is LargeV3. Can I change that by downloading a different version? Do I need to make a change in the command to use a different large model or do I have to remove the folder from Models?
This is what I use:
faster-whisper-xxl.exe File.mp4 --language ja --task transcribe --model large --compute_type auto --device cuda --standard --print_progress --vad_alt_method pyannote_v3 --vad_min_silence_duration_ms 2000
The version model in Faster Whisper is LargeV3. Can I change that by downloading a different version? Do I need to make a change in the command to use a different large model or do I have to remove the folder from Models?
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"large" for the --model will default to whatever the version you're using set it to, but you can specify the specific version to choose it yourself, it's simply an alias that redirects to one of the version.
If I remember right, the correct spelling is "large-v2" where the number can be any of the 3 and it'll download it if it doesn't have it.
Never used faster whisper so I can't comment on it.
If I remember right, the correct spelling is "large-v2" where the number can be any of the 3 and it'll download it if it doesn't have it.
Never used faster whisper so I can't comment on it.
Thanks. Yeah, I managed to find the command info here: https://github.com/Purfview/whisper-standalone-win/discussions/231
I can't seem to fix the Collab problem with recognizing too few lines. I've been told to upload mono tracks so I'm using the recommended ffmpeg command line to convert stereo to mono:
ffmpeg -i input.wav -ar 16000 -ac 1 -c:a pcm_s16le output.wav
It always worked great.
Splitting the audio generated a few more recognized lines (228 > 263) but the result is ridiculous compared to how it was about a year ago when I used it last.
I can't seem to fix the Collab problem with recognizing too few lines. I've been told to upload mono tracks so I'm using the recommended ffmpeg command line to convert stereo to mono:
ffmpeg -i input.wav -ar 16000 -ac 1 -c:a pcm_s16le output.wav
It always worked great.
Splitting the audio generated a few more recognized lines (228 > 263) but the result is ridiculous compared to how it was about a year ago when I used it last.
Whisper will convert the audio to that internally so it doesn't change anything, it's just ideal to do that if you modify the audio since it's a lossless format so you avoid degrading the audio with an extra lossy conversion.
There was a version issue after something updated on the original colab everyone was using here so one that forces the proper versions was made: https://colab.research.google.com/g...AV/blob/main/notebook/WhisperWithVAD_mr.ipynb
Not sure which you're using but that might change something if it's not that one.
How many lines it detects is a pretty bad indicator since medium might simply split up lines more or something like that or it might just makes a ton of mistakes, but I assume you took a closer look to them when comparing.
There was a version issue after something updated on the original colab everyone was using here so one that forces the proper versions was made: https://colab.research.google.com/g...AV/blob/main/notebook/WhisperWithVAD_mr.ipynb
Not sure which you're using but that might change something if it's not that one.
How many lines it detects is a pretty bad indicator since medium might simply split up lines more or something like that or it might just makes a ton of mistakes, but I assume you took a closer look to them when comparing.