We’re building a phone voice agent for Algeria. Current models don’t handle Algerian Darija well, so we want to fine-tune our own. We have a lot of real call recordings, but we’ve never trained a speech model before. Looking for guidance on 4 things: Which model to pick? For speech-to-text and text-to-speech, with a commercial license. How to train it? Fine-tune vs LoRA, what hardware, any good guides or notebooks. What data do we need? How many hours, what format, do transcripts need to be perfect? How to handle different dialects? Algerian Darija isn’t one single accent. It changes a lot between regions: the east (near Tunisia), the west (near Morocco), the capital, and the south all sound different, with different words and pronunciation. Many people also mix in French, and some regions mix in Berber (Amazigh) words. How do we make sure the model understands and speaks all of these? Do we need balanced data from each region, or is one big mixed dataset enough?   submitted by   /u/Fair_Bed_914 [link]   [comments]