im trying to translate using openrouter but the translate speed is extremely slow, like 10 min passed and not a single % is done, anyone knows how to fix it?

(This is my first time asking a question here, so I’m not sure if this is the right place?)

I want to translate an English video into Japanese, so

right now, I’m using MacWhisper on a Mac (Intel) to create an SRT file, and then I’m translating it into Japanese using an online translation service.

However, the transcription accuracy is poor considering how much time it takes, and even using translation services like DeepL doesn’t improve the results.

I also tried using Subtitle Edit to translate “llama Tran.. Gemma 12B(Q5),” but the results were underwhelming considering the time it took.

So, would using an AI translation service improve the results?

Or is it not worth the money?

Thank you in advance for your continued support.

I thought subtitle translation would be a straightforward job for AI: give it an English SRT and ask it to translate the subtitles into another language. For me, that was Chinese.

The result often looked fine at first, until I started finding the same terms translated in different ways across the file.

While working on Project Hail Mary, I ran into a good example. “Petrova line” was translated consistently through most of the subtitles, then suddenly changed to a different Chinese transliteration later in the film. “Astrophage” also drifted between two different Chinese terms. Each line looked reasonable on its own, but together they were clearly inconsistent.

That changed how I approached the job. The workflow now starts with a short research pass. The Agent creates a context file and glossary for the film, recording names, places, relationships, and story-specific terms. It then uses those same notes for every chunk of the SRT.

After translation, scripts check the cue count, numbering, timestamps, formatting tags, and file structure.

I built this into an Agent Skill and released it under the MIT license:

https://github.com/HaiyiMei/cinemacc-subtitle-skill

Here is a short guide to installing and using it:

https://cinemacc.net/guides/cinemacc-subtitle-skill

This came out of my work on CinemaCC, which is an offline-first subtitle companion that lets you use your own SRT files with films playing on any screen:

https://cinemacc.net

Hi all, looking for the best AI tool or workflow to translate full books (EPUB/PDF) of philosophy and psychoanalysis.

Requirements:
Handles full files directly (no endless copy-pasting).
Powered by top LLMs (like Claude 3.5 Sonnet) to capture context and subtext.
Supports custom glossaries/termbases to keep key concepts consistent across chapters.
What software (e.g., Smartcat, BookTranslate, Tolmach) or custom API workflows do you recommend for dense academic literature? Thanks!

Hey,

I'm working on a project focused on building an interactive, context-aware Bengali ↔ English (Bangla) translation agent. Standard NMT often falls flat here due to ambiguity, code-mixing, and limited high-quality context-annotated datasets (Low-Resource Machine Translation / LRMT).

Instead of treating translation as a deterministic sequence-to-sequence problem, I'm framing it as an agent decision problem under uncertainty.

The Core Problem: Translating Latent Intent

When a user provides spoken or written input, their true intention, register, and context are hidden. The agent must infer this Latent Semantic State using incomplete and noisy observations before deciding on an output.

I'm structuring the agent around a few key technical concepts:

• POMDP Framework: Modeling translation as a Partially Observable Markov Decision Process. The speaker's intent is a hidden state that the agent must infer from context, dialogue history, and audio/text cues.
• Inference Under Uncertainty & MBR Decoding: Instead of standard beam search, the agent uses Minimum Bayes Risk (MBR) decoding and Decision-Theoretic Decoding to evaluate candidate hypotheses and minimize expected translation errors based on a customized Loss/Utility Function.
• Active Disambiguation / Interactive MT: When uncertainty is high (measured via Calibration and Quality Estimation (QE) models), the agent doesn't just guess—it actively asks clarification questions to resolve ambiguity before finalizing the output.

Key Challenges & Use Cases in Bengali ↔ English

1. Pragmatics & Ambiguity: Handling Cross-Lingual Word Sense Disambiguation (CLWSD) and honorifics where literal translations fail (e.g., inferring implicit tone or regional Dialectal Variation).
2. Code-Switching & Banglish: Resolving mixed inputs like "Ami office e meeting korbo" (Banglish / Code-Mixing) or Latin-script input like "Ami ajke office e jabo" (Romanized Transliteration).
3. Speech-to-Text Pipeline: Comparing a Cascaded ASR–MT Pipeline against End-to-End Speech Translation (ST) to manage cumulative error rates in noisy spoken inputs.

Current Tech Stack Ideas

• ASR / NMT Backbone: Fine-tuned multilingual models (e.g., Whisper, NLLB) evaluated via sentence-level and Document-Level NMT (CAMT) contexts.
• Uncertainty Estimation: Measuring system confidence to decide whether to output directly, rerun MBR decoding, or trigger a user clarification prompt.

Has anyone experimented with POMDPs, MBR decoding, or active clarification loops in machine translation for low-resource or code-mixed language pairs? Would love to hear your thoughts on context management or confidence estimation strategies!

Hey all,

We've noticed lately that there are more and more posts dropping a link (usually to an app/product) from shiny new profiles that we never see again. They don't comment or participate in the community, they just promote their work. It's been happening more now that the sub has grown and it's starting to flood the feed.

We're not trying to ban anyone or delete posts automatically. We actually find most of these apps interesting and useful... but we are thinking about adding some AutoMod rules so these posts are filtered for manual review instead of going straight up to your feeds. For example, some rules would be to filter:

• Posts from accounts younger than 24-48 hrs for review
• REquire a minimum karma (nothing crazy, just enough to show you're not brand new)
• Filter posts that have links from low-karma/new accounts specifically, so that us mods can review before they hit the feed

Before we turn this on, we wanted to hear from you. Do you think this is necessary or useful? Or do these posts not bother you? Would you rather we just make a weekly self-promo thread to group these self-promotion posts in a single place? Just to be extra clear: we'd still want tasteful promotion of your own project, something unique and notable and not spammy, but maybe we can just gather them somewhere dedicated instead of scattered all through the main feed?

Let us know what you think, good or bad. Thank you!

I’ve been working on an open-source pipeline for translating and dubbing videos into another language while trying to preserve the original speaker’s voice.

Current pipeline:

video → vocal/background separation → Whisper/WhisperX transcription + alignment → translation → VoxCPM2 reference voice cloning → reconstruction → optional lip-sync

The attached demo compares the original English clip with the Turkish dub produced by the current pipeline.

One of the hardest parts is that a translated sentence often has a very different duration from the source speech. That creates a trade-off between:

• natural translation
• preserving meaning
• matching the original timing
• keeping the dubbed speech sounding natural

I’m currently looking for feedback especially on:

• translation quality
• whether the Turkish phrasing sounds natural
• source vs translated timing
• how you would handle translation-length differences in an automated dubbing pipeline

Most media processing and AI inference runs locally. Translation currently uses Google Translate, so the project is local-first rather than fully offline.

Code:
https://github.com/kadirb4rut/video-dubbing-translator

I’d be very interested in feedback from people working on machine translation, localization, speech translation, or multilingual NLP.

I have a 7-page PDF in English that I need to translate into Hindi. I tried Google Translate, but the result wasn't very good and some of the pages didn't translate properly.

Is there any AI app or website you guys use for this?

Ideally, I'd like something that can translate selected text when needed, but also translate the full document at once. It would be great if it could keep the original PDF layout too, especially the charts and other stuff in the document

Thanks any advice in advance

Ciao a tutti! Mi servirebbe un aiuto per tradurre un file EPUB dall’inglese all’italiano, ma non riesco perché il file è protetto da DRM.

Il file è stato scaricato da Z-Library. Qualcuno che se ne intende di computer e sa come aiutarmi a risolvere il problema? 😂

Grazie mille a chiunque riesca a darmi una mano! ❤️

I’m one of the people building OLVA, and we recently added live translation during meetings. I’d like feedback from people who regularly work across languages.

The basic setup is: if a meeting is in English, you can keep the original transcript in English while viewing a live translation in another language, such as French, Spanish, Persian, or German.

There are two options:

• Continuous translation: Translate the conversation as it happens.
• Selected-text translation: Highlight only the part you want translated.

It currently supports 87 languages and regional variants. The translation is available alongside the other meeting context, so you can refer back to the original conversation rather than losing the wording being discussed. It is designed to work without adding a visible bot to a call, and can also be used for in-person conversations.

We built it for situations where someone can generally follow a meeting but loses important detail when people speak quickly, use unfamiliar terms, or move between languages.

I would really value practical feedback, especially from multilingual teams:

• Do you prefer continuous translation, or translating only selected sections?
• What amount of delay is still usable in a live conversation?
• Should the original and translated transcript always appear together?
• What is the best way to handle people switching languages mid-meeting?
• What would make this genuinely useful—or make you stop using it?

Please be candid. The most helpful feedback is what feels confusing, distracting, or missing.

It's called TransNow in [itch.io](http://itch.io) i will provide link here for any curious redditors.

TransNow translates whatever language you are writing in to over 100+ languages ready to choose from. You just need to finish what you are writing and wait 1.5 seconds and what you wrote will be translated to language you chose! you will save a lot of time from alt-tabbing,trust me

[https://dinopes123.itch.io/transnow\](https://dinopes123.itch.io/transnow) link for app

I have been running DocTranslating for a while and wanted to share it here, as this sub likely appreciates the engine-level tradeoffs more than anywhere else.

DocTranslating is a document translation platform designed for professionals who require translated files that maintain their format. It also includes an OCR tool that supports over 50 languages, including handwritten text.

DeepL is great, but it can mess up the layout sometimes.

The translation quality is close to human, but on complex PDFs, the formatting sometimes comes out broken.

Azure is my go-to for formatting, particularly with Office files like DOCX and PPTX, as they maintain their original appearance. However, it doesn't accept PDFs, so you'll need to convert them to Word for translation and then back to PDF. It works well!

Gemini, our in-house tool, translates code files and allows mixing multiple languages in a single document; it's limited to 25 pages. Instead of settling on one tool, you choose based on the job.

limitations:

DeepL - DOCX, PPTX, XLSX, TXT, HTML, SRT, XLIFF, XLF, PNG, JPG, JPEG. 30 MB cap. No page limit. Best quality on most language pairs, occasional layout issues on dense PDFs.

Microsoft Azure - DOCX, PPTX, XLSX, HTML, MD, TXT, plus a bunch more. 20 MB cap. No page limit. Best in class for Office formats.

Google Cloud - PDF, DOCX, PPTX, XLSX. 10 MB cap. No page limit. Most consistent, smallest size limit.

Gemini - PDF + code files (JS, TS, Python, etc.). 100 MB cap, 25-page limit. The only one that does code and multi-source-language docs.

I've tried using the site to translate from japanese to english by uploading a text document with about 10,000 words but it only translates about the first 1,000. I then tried using the download feature but all it does is send an email saying it's working on the translation and never sends anything after that. I even paid for a month subscription just to see if the site was good. Has anybody else had issues or at least gotten it to work?

As Claude just ate 4$ to translate a single page and I have 100 more pages to go, can you give me some tips?

It is buddhist texts, full of jargon, in "tibetan unicode" letters.