Generative audio and voice AI covers tools that synthesize, transcribe, clone and manage human speech for applications such as voice agents, dubbing, meeting capture, accessibility and content production. By 2026 this category has moved from demos to production deployments: low-latency APIs, studio-grade text-to-speech, and integrated speech-to-text pipelines are now common requirements for enterprises and creators. Key offerings illustrate the landscape: ElevenLabs focuses on high-fidelity expressive TTS, voice cloning and transcription for production audio and voice agents; Murf AI delivers studio-grade TTS, multilingual dubbing and real-time voice APIs; Recall.ai provides APIs/SDKs to capture, transcribe and surface meeting recordings and metadata from Zoom, Meet and Teams; Krisp emphasizes call-quality features—noise suppression, real-time transcription and accent conversion; and several platforms (ZenCall.ai, OpenCall AI, Simple Phones) package speech-to-text + LLMs + TTS into AI phone agents for customer service, scheduling and healthcare workflows (OpenCall AI explicitly targets HIPAA-compliant automation). Practical decision factors in 2026 include audio realism, latency, multilingual coverage, integration points (SDKs, conferencing and CRM connectors), developer APIs, and regulatory or privacy constraints (consent, deepfake risk, HIPAA). While AI-generated music and sonic design remain adjacent categories for soundtracks and branding, core buying criteria for voice systems focus on reliability, verifiable provenance, and safe deployment. Organizations evaluating tools should weigh fidelity against compliance, real-time needs, and ease of integration to choose the right mix of synthesis, transcription and voice-agent capabilities.