I develop high-performance voice applications that run in real time, handle heavy workloads, and maintain stable, low-latency performance even at global scale.

Many developers already rely on my open-source libraries (like RealtimeSTT, RealtimeTTS and Linguflex) for accurate, responsive transcription and text-to-speech.

My services include:

• Setting up end-to-end real-time speech recognition and TTS pipelines for multi-user, low-latency environments.
• Implementing GPU optimization, load balancing, and runtime configuration for scaling under heavy traffic.
• Integrating various TTS engines (e.g. Coqui, StyleTTS2, Azure, ElevenLabs, ... ) and fine-tuning them for quality and speed.
• Applying sophisticated audio chunking, compression, and sentence logic to improve transcription accuracy and responsiveness.
• Enabling real-time streaming via browser-based clients with stable, continuous, and natural-sounding output.
• Integrating voice activity detection (VAD), wake-word recognition, and other advanced speech features.
• Incorporating large language models to support streaming tool-calling, contextual responses, and dynamic memory or RAG workflows.
• Offering reliable backend infrastructure advice, including containerization and orchestration (e.g. Modal, Runpod, Kubernetes) for global-scale operations.
• Providing guidance on tuning parameters to ensure optimal audio quality, stable performance, and minimal latency.
• Advising on training data and model selection to achieve fast, robust, and context-aware results in speech and language tasks.

If you’re looking for someone to implement or enhance voice features quickly, reliably, and at scale, you’re more than welcome to contact me at [email protected].