Generative audio and speech AI now spans production-grade text-to-speech, voice cloning, real-time transcription, conversational voice agents, and meeting intelligence. As of 2026 these capabilities are widely deployed across content studios, contact centers, healthcare workflows and productivity tools. Key technical trends include ultra‑realistic TTS and cloned voices for dubbing and voiceovers (ElevenLabs, Murf AI, Podcastle), low‑latency voice agents and HIPAA-compliant telephony for bookings and patient outreach (OpenCall AI, Simple Phones, VOICEplug), and robust meeting capture and analysis via APIs and SDKs (Fireflies, Recall.ai). Tools such as Krisp focus on front‑end audio quality—noise cancellation, accent conversion and real‑time preprocessing—that improve downstream ASR and user experience. This topic is timely because advances in model fidelity, multilingual support, and deployment (cloud and edge) have shifted generative audio from experimentation to integrated workflows. Enterprises are balancing utility with compliance and safety: HIPAA and consent requirements, deepfake mitigation, and guardrails for voice cloning influence vendor selection. Developers and content teams now evaluate platforms on voice naturalness, language coverage, latency, developer APIs, transcription accuracy, metadata and searchability of recordings, and integration with conferencing systems. AI music creation and language tutor applications—though driven by somewhat different models—leverage the same synthesis and processing building blocks for personalized practice, adaptive feedback, and automated scoring. This overview helps buyers and practitioners compare categories and vendor strengths: expressive TTS and cloning (ElevenLabs, Murf, Podcastle), meeting assistants and recording platforms (Fireflies, Recall.ai), audio quality and preprocessing (Krisp), and vertical voice automation (OpenCall AI, VOICEplug, Simple Phones, AI Phone).