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Learn how to run LLMs locally in C across Linux, Windows, macOS, and Raspberry Pi with streaming text generation.

Step-by-step guide to adding speaker diarization to OpenAI Whisper STT in C++ using Falcon Speaker Diarization for multi-speaker transcription.

Voice Activity Detection (VAD) is a core building block for speech and audio systems, used to determine when human speech is present in an audio stream.

Learn how to implement real-time noise cancellation in C across Linux, Windows, macOS, and Raspberry Pi.

Learn how to build a local MCP voice assistant using a local LLM to handle function calling, speech-to-text, text-to-speech, and external API integration in this step-by-step MCP tutorial.

Build a banking voice AI agent with custom wake words and voice activated banking features for secure and compliant financial applications.

Learn how to get word-level confidence scores in Python for speech-to-text. Set word confidence thresholds to improve transcription quality.

Step-by-step tutorial: Build cross-platform speaker recognition in C using Picovoice Eagle. Includes complete code for speaker enrollment & recognition on Linux, Windows, macOS, and Raspberry Pi.

The term "AI OS" is everywhere, but its meaning varies widely depending on who you ask. This guide explains what an AI operating system is, how it compares to traditional OSes, popular examples in the market (AIOS, CosmOS, Tesla FSD, etc), from marketing stacks to research‑grade frameworks, and why multiple definitions exist.

AI text completion (or AI autocomplete) uses language models to predict the most probable next words, phrases, or sentences based on the current context. Unlike traditional autocomplete that relies on static dictionaries, modern autocomplete solutions understand semantics and intent to generate contextually relevant suggestions in real-time.

2025 was another transformative year at Picovoice. We expanded our multilingual capabilities across core engines, introduced breakthrough performance optimizations, and grew revenue by 5x while maintaining our commitment to best-in-class on-device voice AI.

Enterprise teams deploying translation on mobile and embedded devices face limited SDK options. Google ML Kit and Apple Translation have platform restrictions and branding requirements.

Voice isolators separate human speech from background noise in real time. For real-time apps, developer SDKs like Koala Noise Suppression offer cross-platform support with low latency and self-service integration.

Learn how to implement cross-platform voice control in C using Rhino Speech-to-Intent for real-time on-device intent recognition.

Learn how to implement on-device wake word detection in C across Linux, Windows, macOS, and Raspberry Pi.

Everything you need to know about Text-to-Speech technology: how it works, why it matters, and how to build natural-sounding voice experiences.