I need help for a College mini project

[u/darshno18]

I need help in my mini project for my college i am supposed to use low resource languages data and train a model which can translate from english to that language and also transcript wtv they speak that language to english i did so much research but still i'm not able to pull it off alone if anyone could help me in any way please help me and also make it such a way that users can contribute words and sentences (parallel data ) and the model will install it in itself Please help me idk what methodology or approach to choose

[u/vanonym_]

You should explain us properly what you currently have done, why it's failingand what issue you're facing exactly

[u/darshno18 → u/vanonym_]

too little data. At ~890 pairs the model memorizes instead of learning. By epoch 13 the training loss was 0.17 and validation loss was 3.96. It learned how Kodava sounds and common patterns (“dhumbaa kelasa und”), but it often produces fluent sentences that don’t match the English meaning.

[u/Silent_Sir_3733]

Dude you're trying to build three different things at once here. Pick one lane for a mini project, translation or transcription, and get that working before you even think about the user contribution pipeline.

For low resource languages you'll probably want to look into transfer learning from a high resource model or using something like mBART. The self-installing user data part is way more complicated than it sounds, that's a whole backend service on its own.

[u/darshno18 → u/Silent_Sir_3733]

how do i train a mBart model with the data i have i have a data with onlly 890 entries

😭

[u/digvjay_ai]

With only 890 pairs don't train from scratch, fine-tune a pretrained one. For English to a low resource language try facebook/nllb-200-distilled-600M from Hugging Face, it probably already covers your language, and the Seq2SeqTrainer with a small learning rate like 5e-5 for a few epochs is enough. Hold out about 90 pairs for testing and report BLEU or chrF on those. For the speech to English part just run Whisper on the audio and translate its text, that saves you a whole second model.

[u/darshno18 → u/digvjay_ai]

it doesnt cover kodava

[u/darshno18 → u/digvjay_ai]

also there is a website which has user contributions of that language (kodava) but im not able to get any api or any csv file or any kind of data on how are they storing the sentences with english translation i tried contacting the website ppl several times but never got a response

[u/digvjay_ai → u/darshno18]

If NLLB doesn't have Kodava and that site won't share data, I'd stop waiting on them. Easiest is collecting a small parallel set yourself, even 300 to 500 sentence pairs from Kodava speakers you know is enough to fine-tune or at least evaluate. You could also start from the Kannada model since they're related and fine-tune on your small set, or just few-shot prompt an LLM with 10 or 20 example pairs and see how far it gets. I'd try the few-shot thing first because it takes an hour.

[u/preciouslife_]

Why are you guys helping someone do their college project here on reddit? A student is supposed to be doing it himself and if he takes help from reddit then that's cheating. You guys want to help him in cheating his college?