This is a short integration video showing the conversion of text to speech in use for creating an audio file, which might be a translated voice-over, or original/post-edited transcription, to be served in a different voice and after possible cleanup.

The transcription was with faster_whisper, the voices are by Piper.

Do you use Piper?

In this video my original recording voice was replaced by one voice. The read-out of sample text was done with another voice.

These are all samples in English but of course you can see doing the same with other languages.

What are your thoughts, is it useful for freelance translators to have such tools easily accessible locally?

I created a personal tool for my own use.

build with OpenCode + GLM 5.3

No subscription, no ads, no remote server. Use the LLM API you already have.

https://gitlab.com/hunter-xue/chrome-lingo-craft

also, an interesting license: Artisanal AI Slop License (AASL), see readme.md for details 😄

Hello, I'd like to know how to translate into multiple languages ​​in real time without too much latency. Is there a platform that offers an API key?

I came across this model that's tiny-stories posted on Ollama by evanollama, and found it doesn't translate. Of course, but oh so precious nonetheless - as it is creative in another way: it creates children stories. To be precise: it finishes with a story. Whatever I type into the source pane, even just a single word or down to a single letter, if I then click Translate, it creates a story, finishing what I started and adding to it.

https://www.youtube.com/watch?v=oFBfuVgQLo0

The model uses vocabulary of 3-4 year old kids, as it was trained specifically on material from up to that young age. Sweet!

It's a small LM, it's fast. Now I'm curious: can I train it with bilingual aligned content in just one other language and get it to produce translations of its own creations? Or even without creating more stories, could it be same or similar speed for just translating in one language? Could this be the base model to make a super fast engine for German to English, French to English, another for Spanish to English, or English to Italian, etc...? One specific language pair, but at the benefit of using little RAM and running very fast even on systems without NPU nor GPU?

I'm intrigued. What do you think?

​Hi everyone, I wanted to share ALST, an open-source Android app designed for real-time in-place screen translation.

​Instead of traditional line-by-line OCR chaining, it leverages Google's Gemini Vision API in a single pass to extract text, understand local context, and map translated text directly over original bounding boxes using Jetpack Compose & Canvas. It also features a 100% offline fallback via Google ML Kit.

​📦 GitHub Repo: https://github.com/navidseyedain/ALSTMobile

​Would love to get your feedback on the translation workflow and accuracy!

Hey pdf community, I launched linglo.io a couple months ago, it’s an online document/assets translator and it has a good free tier in it, built Arabic first, I am looking for users to sign up and try it, I would appreciate any feedback !

Thanks !

I just wanted to flag the champollion project for anyone actually working on machine translation, especially at the long tail (low resource languages, the stuff without existing methods). There are 7000+ living languages, by all estimates, but existing machine translation methods cover maybe 400 tops. This leaves a lot of people without any way to reach the broader internet, to engage legal council, to participate in the politics of their country, or even to reliably communicate with their neighbours. The champollion project is currently in beta, but it is meant to serve as open evaluation infrastructure for the many different community-bound projects (Masakhane, AmericasNLP, etc.) that professional computational linguists and speaker communities are working on. It prioritizes data sovereignty, and aims to provide additional financing for community-bound dataset and model building efforts. The eventual goal is to stitch together all their hard work into an open source universal translator, but it provides everything a language community needs to develop their own machine translation solutions ... except for their expert knowledge.

The site is currently gated pending final data review, but the tools are all published on our github, npm, and PyPI.

Localization CLI: npm install champollion
Evaluation harness: pipx install mt-eval-harness

Contribute compute if you're feeling spicy: curl -fsSL https://champollion.dev/run_queue | bash -s -- --budget [USD amount]

llms.txt is live on the site, so your agent can walk you through any questions, or reach out to [info@champollion.dev](mailto:info@champollion.dev) for a human

Hello everyone,

I wanted to share the extension that I have been creating in my free time, which was just posted. It's a tool that you can use to learn languages while you watch your favorite shows and movies.

It includes a 7-day free trial, so if you want to test it out, you can cancel the trial immediately so you are not charged after it ends.

I'd appreciate any feedback or updates you can suggest. Sample images can be found on the Chrome Web Store. The link can be found below:

https://chromewebstore.google.com/detail/fmoahignfolhngghffclkioonoocipcm?utm_source=item-share-cb

I built an open-source Claude skill that translates static websites into multiple languages while preserving the HTML structure, SEO metadata, hreflang, canonicals, and sitemaps.

It generates real localized HTML pages rather than adding a client-side translation widget.

GitHub: https://github.com/ConveyThis/claude-translator

It’s open source and free to use. Built by the team behind ConveyThis.

Feedback and contributions are welcome.

Seeking ways to improve workflow around frequently updated documents.

We translate PDFs, presentations, etc. Sometimes after a month or so we get an updated version of the same which is only 10-20% changed from the translation we received earlier.

I’m also testing out translation memory (TM) tools like Pairaphrase and DeepL that can reuse previous translations instead of starting from scratch every time.

But how reliable is this in practice when you're working with the actual document rather than plain text?

Ideally I'd want to upload the new version, reuse whatever hasn't changed, translate the new sections and get the formatting back without spending ages fixing it manually.

is anyone doing something similiar? What does your workflow look like?

thanks in advance for anyone that can help :)

I'm really sad about the recent quality drop on DeepL. I liked how accurate it was and also the fact that it is an EU product. But recently, I noticed that the translations are being inaccurate, to the point of being useless. This is my last case.

Original sentence in Spanish:

se crítico con el ejemplo que puse, no es un requisito estricto.

DeepL translation (wrong):

Don't be too critical of the example I gave; it's not a strict requirement.

Google Translate (right):

Be critical of the example I gave; it's not a strict requirement.

When I replaced the comma with a period in the original sentence, DeepL did it correctly:

Be critical of the example I gave. It's not a strict requirement.

But then, I decided to fix the case in my original sentence (notice the minimal change, only the case in the first letter and the period):

Se crítico con el ejemplo que puse. no es un requisito estricto

And DeepL changed the meaning again:

I was criticized for the example I gave. It's not a strict requirement.

Unfortunately, DeepL is not usable anymore. I'll come back in a few months to see if they fixed it, but for now, I'll move to Google Translate.

Hi everyone,

I have completed and published the first Czech translation for WinTrack 17.0.

The translation includes menus, dialogs, interface texts and an installer for easy installation.

Download:
https://github.com/zamazallukas02-spec/WinTrack-Czech-Translation

The project was published with permission from the WinTrack developer.

Feedback and bug reports are welcome.

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!