Gesture and Speech AI Development
Budget: $50 – $0 USD
I’m building a multi-modal AI platform that combines real-time gesture recognition, speech-to-text, pose estimation, hand tracking, and facial-expression analysis into a single, production-ready pipeline. The core work revolves around prototyping deep-learning models—leveraging Whisper for speech, Transformer architectures for sequence understanding, and MediaPipe or equivalent stacks for computer-vision preprocessing—then training, evaluating, and iterating until we reach deployment-grade accuracy and latency.
Framework choice is open: PyTorch, TensorFlow, or Keras can all be part of the toolkit as long as the decision is justified by performance or integration benefits. I’ll provide data, annotation guidelines, and any target-device constraints; you’ll architect the model, set up the training pipeline, and refine it through continuous experimentation.
Because this is a long-term partnership, I’ve structured the collaboration around clear milestones:
• Baseline models and benchmarking report
• Optimized versions hitting agreed accuracy/latency targets
• Deployment package (container, mobile build, or embedded runtime) with reproducible inference scripts
Successful delivery of each milestone unlocks the next, giving us room to explore additional modalities or refine current capabilities. If you enjoy pushing state-of-the-art models into real products and see value in an extended collaboration, let’s iterate together on this platform.
Framework choice is open: PyTorch, TensorFlow, or Keras can all be part of the toolkit as long as the decision is justified by performance or integration benefits. I’ll provide data, annotation guidelines, and any target-device constraints; you’ll architect the model, set up the training pipeline, and refine it through continuous experimentation.
Because this is a long-term partnership, I’ve structured the collaboration around clear milestones:
• Baseline models and benchmarking report
• Optimized versions hitting agreed accuracy/latency targets
• Deployment package (container, mobile build, or embedded runtime) with reproducible inference scripts
Successful delivery of each milestone unlocks the next, giving us room to explore additional modalities or refine current capabilities. If you enjoy pushing state-of-the-art models into real products and see value in an extended collaboration, let’s iterate together on this platform.