AI audio and speech platforms combine neural text-to-speech (TTS), voice cloning, speech-to-text (STT) and generative music to automate spoken interfaces, speed content production, and improve accessibility. By 2026 this stack spans production-grade services (realistic TTS and voice cloning), real-time voice agents for phone and contact-center workflows, meeting capture and summarization, and AI-driven music/SFX generation. Key categories and representative tools: ElevenLabs (high-fidelity TTS, expressive voice cloning, transcription and voice agents), Murf AI (multilingual studio-grade TTS and dubbing with developer APIs), Krisp (noise cancellation, real-time transcription and meeting audio enhancement), Recall.ai (capture/transcribe/stream meeting recordings and metadata), and phone-agent platforms such as OpenCall AI, ZenCall.ai and Simple Phones that combine STT + LLMs + TTS for automated call handling. On the generative music side, platforms like Evoke Music/Amadeus Code provide AI toplines, SFX and MIDI generation. Major model efforts (OpenAI–Disney Sora, Google AudioLM, Anthropic audio tools) reflect the industry trend toward higher-quality, character-aware and safety-focused audio models. Why it matters now: latency and fidelity improvements and broad API access have pushed these capabilities into production use for customer service, content localization, accessibility, and creative workflows. At the same time, concerns about consent, copyright, voice provenance and safety (watermarking, licensing, HIPAA compliance in healthcare) are driving product differentiation and regulatory attention. Evaluations should weigh audio quality, real-time performance, multilingual support, developer tooling, privacy/compliance features and provenance controls for responsible deployment.