Voice and audio AI platforms now span production-grade text-to-speech (TTS), high-fidelity voice cloning, real-time transcription, and persistent voice agents that automate scheduling and customer calls. As of 2026, advances in OpenAI audio models and voice-enabled ChatGPT tools have raised expectations for naturalness, low-latency conversational agents, and tighter integration between generative language models and audio pipelines. This topic covers five practical categories: Voice Synthesis and Transcription (realistic TTS and speech-to-text), Text-to-Speech Tools (studio-grade voiceovers and dubbing), AI Language Tutors (spoken practice and feedback), Conversation Intelligence Tools (meeting capture, summaries, analytics), and AI Voice Scheduling (24/7 call handling and appointment booking). Representative platforms include ElevenLabs (expressive TTS, voice cloning, transcription, voice agents), Murf AI (multilingual TTS, dubbing, developer APIs), Podcastle (end-to-end recording, cloning, editing), Krisp (noise suppression, real-time transcription, accent conversion), and Recall.ai (APIs/SDKs to capture and surface meeting audio and metadata). Open-source and specialty options such as Voila (ultra-low latency persona-aware models), Vocea and Sophie (voice assistants for service providers), and OpenCall AI (HIPAA-compliant phone automation) illustrate how vendors are verticalizing for industries and compliance needs. Key trends to evaluate in 2026 are audio quality and latency, transcription accuracy and domain adaptation, API and conferencing integrations, privacy/consent controls (including provenance and watermarking), and regulatory compliance for healthcare and enterprise. Choosing a platform now requires balancing realism, developer flexibility, security, and workflow fit—whether for content production, contact centers, education, or automated scheduling.