Demo: https://www.loom.com/share/a78e713d46934857a2dc88aed1bb100d?...
We started this company after struggling to find great tools to practice speaking Japanese and French. Having a tutor can be awesome, but there are downsides: they can be expensive (since you pay by the hour), difficult to schedule, and have a high upfront cost (finding a tutor you like often forces you to cycle through a few that you don’t).
We wanted something that would talk with us — realistically, in full conversations — and actually help us improve. So we built it ourselves. The app relies on a custom voice AI pipeline combining STT (speech-to-text), TTS (text-to-speech), LLMs, long term memory, interruptions, turn-taking, etc. Getting speech-to-text to work well for learners was one of the hardest parts — especially with accents, multi-lingual sentences, and noisy environments. We now combine Gemini Flash, Whisper, Scribe, and GPT-4o-transcribe to minimize errors and keep the conversation flowing.
We didn’t want to focus too much on gamification. In our experience, that leads to users performing well in the app, achieving long streaks and so on, without actually getting fluent in the language you're wanting to learn.
With ISSEN you instantly speak and immerse yourself in the language, which, while not easy, is a much more efficient way to learn.
We combine this with a word bank and SRS flashcards for new words learned in the AI voice chats, which allows very rapid improvement in both vocabulary and speaking skills. We also create custom curriculums for each student based on goals, interests, and preferences, and fully customizable settings like speed, turn taking, formality, etc.
App: https://issen.com (works on web, iOS, Android) Pricing: 20 min free trial, $20–29/month (depending on duration and specific geography)
We’d love your feedback — on the tech, the UX, or what you’d wish from a tool like this. Thanks!
(probably a more fringe request, but i'm asking because I do all my language learning on the commuter trains w/o a good connection.)
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.