Lately I’ve noticed that many AI girlfriend platforms have started adding voice features. When I first used CrushOnAI, it didn’t have voice, but now it does, and many other platforms have had voice chat for a while.
Even so, it seems like a lot of users still prefer text-based conversations for that immersive feeling. This makes me curious from a technical standpoint—what’s really contributing to the depth of interaction? Is it more about text-focused training, multi-turn memory, or can voice input/output truly enhance the emotional experience in a similar way?
I’m also wondering how different platforms handle this. CrushOnAI is one of the larger platforms and now supports voice, but does that change how the AI maintains context or emotional cues compared to purely text-based models?
Has anyone experimented with these aspects or has insights on whether text, voice, or a combination is better for building that sense of real connection in AI companions? Would love to hear your technical thoughts.
I’ve noticed that many platforms have also added image interactions. Personally, I feel that combining text and images creates a more authentic experience. Especially when AI can send pictures, it feels more like chatting with a real girlfriend. On the other hand, with voice, some products still have pretty robotic-sounding voices, which can break the immersion.
I’ve used the feature where AI sends pictures to me too, and I agree, it’s a nice design! It definitely adds to the experience. But sometimes, I do wish the AI could initiate messages on its own. Right now, it feels like I’m the one always starting the conversation, which gives it a bit of a “bot” vibe. Would be interesting if it could take more initiative!
You probably didn’t think of anything else. Not everyone’s native language is English. For such people, it is especially easier to communicate with the model as text where you can also use a translation program. If you can’t speak English well, understand it, or both, why choose to communicate with speech?
That’s a fresh perspective! You’re right, many platforms offer multilingual support for text, but not necessarily for speech models. So, it can definitely be a bit tricky in that sense.
When adding audio input/output to an LLM, the current common approach is to use external components like Whisper for speech recognition (ASR) and text-to-speech (TTS) for audio output. There are many good TTS options available.
On the other hand, there’s the approach of adding a head directly to the LLM itself, similar to how Vision Language Models (VLMs) handle images, to create a multimodal model.
Hugging Face already has several such models… Once these become more refined, voice input/output based on the same neural network as the LLM itself—rather than external components—will likely become practical.