mariano54

Joined 12 years ago

Karma
227
Submissions
54
Member since
Jan 27
[ my public key: https://keybase.io/sorgente711; my proof: https://keybase.io/sorgente711/sigs/0FfsWAJ4HsSbHCxWWx5dllFSukMBdqUqJhsx30h0DYM ]
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Recent submissions

Comment · 16 days ago
This is amazing. Feels like it will be the start of a new era for interpretability research
Comment · 2 months ago
Just added this to my benchmark site: https://multilingualsttbench.com/

It doesn't reach the frontier in either latency or accuracy for ai multilingual conversations.

Comment · 1 year ago
I'm sorry but we are not providing longer free trials at the moment. You can clear the cache to try again (but you will have to go through the onboarding).
Comment · 1 year ago
Comment · 1 year ago
Thanks for the feedback.

1. The response latency / patience can be configured in the quick settings (tap the gear during the call).

2. There already is a bias in transcription. It's something we're actively improving, multilingual transcription isn't a solved problem yet

3. It is supposed to correct you actively if you have corrections enabled (check the settings). But we received feedback that it's not enough, so we will ramp it up soon

Comment · 1 year ago
Yes it pushes the problem, but it's a much easier problem, and models like Gemini flash 2.5 do very well.
Comment · 1 year ago
The mobile app can be used in a car (not the Web app). Looking at the screen is not required.
Comment · 1 year ago
Minimax's new model is quite good. We use their voices for some of our Japanese tutors. The pitch accent is almost perfect.

There are incorrect reading or Chinese readings occasionally, but you can tell when that happens due to the furigana being different

Comment · 1 year ago
I'm sorry about that. May I ask what language you tried?
Comment · 1 year ago
Thanks for pointing that out. Did you try the other ones by any chance?
Comment · 1 year ago
Langua is a nice app with more features than ISSEN. We focus on the voice chats, and I think our tech is better (intelligence, latency, realtime flow, voices, etc), especially for non english/spanish.

We are aiming to create a long term companion/tutor that gets to know you more and more, and can create customized curriculums, lessons, etc.

Comment · 1 year ago
Our market is different - ISSEN is more focused on intermediate and advanced students, and especially those that are willing to use a more difficult app in order to learn faster.

Also, having the AI voice tutor as our main feature allows us to iterate quickly, and be well positioned for future improvements in AI models.

As for marketing and GTM, we're in the super early stages, and there is definitely a lot of competition out there, it won't be easy.

Comment · 1 year ago
The persuasion lesson sounds like a great idea, we haven't thought of that. Yeah voice to voice models will be amazing. There is significant progress from openai/gemini, and we plan to use them when they are ready.
Comment · 1 year ago
Exactly, it's all server side. There are no plans for this. The main issue I see with doing it in device is the LLM piece. Even with some large models like llama 4 maverick, the tutor just struggles to properly teach and understand the student, it's not viable IMO.

Intelligence is super key here, especially as the context size gets larger (due to memory) and intelligence degrades.

Another major issue is TTS voice quality, but this seems to be improving a lot for small local models.

EDIT: You're right, latency is also a big deal. You need to get each piece under a second, and the LLM part would be especially slow on mobile devices.

Comment · 1 year ago
Thank you so much for that!

We focused on testing and tweaking the most popular ones, we have not tested some of the niche ones. We have removed languages that users have told us have major issues, but there are still some left.

The voices are due to the quality of the TTS services that we use. Openi, 11labs, minimax. Some services don't have many or even 1 good voice. We will add more over time

Sesame also passes in the users voice into the TTS model so that it can vibe well with the users tone and mood, whereas we are just using raw TTS. Their latency is also very low, but this is not quite suitable for language learning.

In the future we hope to move to full voice to voice models, once those become mature and intelligent enough.

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