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Products that do what Voice gender classifier for European voice AI (1MB, ONNX, 4ms) does
Hi, I'm Kamil and I'm a founder of Applied AI agency in Warsaw, Poland. We've trained a small <1MB voice classifier model that runs on CPU in 4ms. Can be run next to silero VAD in voice AI deployments. What we noticed in production deployments of voice assistants in Contact Centers in EU is that human consultants pick up immediately how to inflect verbs and ajdectives after one utterance from the caller. But voice AI agents don't know it until 1-2 minutes into the call when they are either corrected or the caller uses explicitly words with male/female form a couple of times. Our model…
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2025 · github.com
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Last year when GPT-4 was released I started making lots of little voice + LLM experiments. Voice interfaces are fun; there are several interesting new problem spaces to explore. I'm convinced that voice is going to be a bigger and bigger part of how we all interact with generative AI. But one thing that's hard, today, is building voice bots that respond as quickly as humans do in conversation. A 500ms voice-to-voice response time is just barely possible with today's AI models. You can get down to 500ms if you: host transcription, LLM inference, and voice generation all together in one place;…
2024 · fastvoiceagent.cerebrium.ai
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I built a voice agent from scratch that averages ~400ms end-to-end latency (phone stop → first syllable). That’s with full STT → LLM → TTS in the loop, clean barge-ins, and no precomputed responses. What moved the needle: Voice is a turn-taking problem, not a transcription problem. VAD alone fails; you need semantic end-of-turn detection. The system reduces to one loop: speaking vs listening. The two transitions - cancel instantly on barge-in, respond instantly on end-of-turn - define the experience. STT → LLM → TTS must stream. Sequential pipelines are dead on arrival for natural…
Mar 2026 · ntik.me
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TLDR: We created a personalised Andrej Karpathy tutor that can response to questions about his Youtube videos in sub 1 second responses (voice-to-voice). We do this using a voice enabled RAG agent. See later in the post for demo link, Github Repo and blog write up. A few weeks ago we released the worlds fastest voice bot, achieving 500ms voice-to-voice response times, including a 200ms delay waiting for a user to stop speaking. After reaching the front page of HN, we thought about how we could take this a step further based on feedback we were getting from the community. Many companies were…
2024 · educationbot.cerebrium.ai
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First TTS model to support all 22 Indic languages + English
2024
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Learn English, Spanish, German, French & more by talking
2024
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Our goal with this project is to build a completely open source, state of the art turn detection model that can be used in any voice AI application. I've been experimenting with LLM voice conversations since GPT-4 was first released. (There's a previous front page Show HN about Pipecat, the open source voice AI orchestration framework I work on. [1]) It's been almost two years, and for most of that time, I've been expecting that someone would "solve" turn detection. We all built initial, pretty good 80/20 versions of turn detection on top of VAD (voice activity detection) models. And…
2025 · github.com
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