voice▌

Skill by ara.so — Daily 2026 Skills collection.

Natural conversation with AI through speech, balancing latency against control. \n \n Choose between speech-to-speech models (lowest latency, less controllable) or pipeline architectures (STT→LLM→TTS for fine-grained control) \n Core challenges: latency budgeting across all components, voice activity detection, barge-in handling, and turn-taking to avoid awkward pauses or overlaps \n Requires semantic VAD, response length constraints in prompts, and noise handling to achieve natural conversation

Real-time voice AI applications with OpenAI Realtime API, Vapi agents, and best-in-class STT/TTS providers. \n \n Covers three primary architectures: native OpenAI Realtime API for integrated voice-to-voice, Vapi for hosted phone and web agents, and modular pipelines combining Deepgram STT with ElevenLabs TTS \n Emphasizes streaming at every layer (interim transcription, token-level LLM output, chunked audio synthesis) to minimize latency and preserve conversation flow \n Includes barge-in detec

Apply existing brand guidelines to all sales and marketing content generation. Load the user's brand guidelines, apply voice constants and tone flexes to the content request, validate output, and explain brand choices.

Use the bundled scripts. Configure DASHSCOPE_API_KEY in one of:

Remove background noise and isolate vocals from audio files via inference.sh CLI. \n \n Supports five audio formats (WAV, MP3, FLAC, OGG, AAC) up to 500MB and 1 hour duration \n Removes ambient noise, background music, reverb, wind, traffic, electrical hum, and other non-voice sounds \n Integrates into multi-step workflows for transcription, voice transformation, and video production \n Requires inference.sh CLI ( infsh ) installation and login to run \n

Transform any voice into a different voice while preserving speech content and emotion. \n \n Supports two models: multilingual STS v2 (70+ languages) and English-optimized STS v2 \n Access to 22+ premium voices across multiple styles and accents (British, American, Australian, and more) \n Configurable output formats and seamless integration with media workflows for voice-over replacement and character creation \n Requires inference.sh CLI ( infsh ) for command-line execution \n

Create ElevenLabs Conversational AI voice agents for client discovery, feedback, and check-in calls. Automatically generates agent configuration from client context.

Add human warmth, emotion, and natural speech patterns to AI voice output. \n \n Includes five speaking presets (good night, good morning, comfort, celebration, just chatting) that automatically tune pace, warmth, and emotional tone \n Sprinkle non-lexical fillers (hmm, aww, haha, sighs) at natural pauses to create conversational authenticity; supports up to 4 fillers per short message \n Clone specific character voices by providing reference audio from YouTube clips or personal recordings, forw

You are a voice AI architect who has shipped production voice agents handling millions of calls. You understand the physics of latency - every component adds milliseconds, and the sum determines whether conversations feel natural or awkward.