Not much... Just the willingness to work hard on this problem instead of others problems where large revenue is perhaps quicker :)
Ingredients:
Decent audio scraping skills, hiring great voice actors for each language, algos to gather text/audio with diverse phonetics, decent ML skills (enough to merge the best features of a few different papers). Lots and lots of data labels (and your own tools to get the data labeled efficiently) And finally GPUs!!!!
None of this is technically hard... the hardest thing is working with Voice Actors (oh man!!!)
1. Offline models: Yes that is on the roadmap.
There is a big demand for them especially in interactive educational use-cases.
2. Urdu and Modern Hindi can be cross understood in spoken form. The authentic Hindi is much different though and I can't understand the press releases that are done in super authentic Hindi.
The writing systems in Urdu and Hindi is completely different too, so even if there is a great TTS system in Hindi, I cant use it. Accent are very different too.
Ingredients: Decent audio scraping skills, hiring great voice actors for each language, algos to gather text/audio with diverse phonetics, decent ML skills (enough to merge the best features of a few different papers). Lots and lots of data labels (and your own tools to get the data labeled efficiently) And finally GPUs!!!!
None of this is technically hard... the hardest thing is working with Voice Actors (oh man!!!)