This topic covers the current landscape of AI audio technology — from speech-to-text and real-time text-to-speech to voice cloning and conversation-intelligence SDKs — with a focus on tools developers and creators use in 2026. Driven by faster streaming models, lower-latency voice stacks, and broader adoption of audio agents, the field now spans production-grade TTS, browser- and mobile-first dictation, meeting capture, and open-source systems for persona-aware dialogue. Key tool types and examples include: production TTS and cloning (ElevenLabs — expressive TTS, high-fidelity voice cloning, and transcription), all-in-one audio studios for creators (Podcastle/Async — recording, multi-track editing, dubbing, subtitles, voice cloning), open-source real-time voice models (Voila — low-latency, persona-aware full‑duplex interactions ~195 ms), lightweight browser dictation (BlabbyAI, Transcribe Audio), meeting capture and metadata APIs (Recall.ai), and mobile-first note capture and structuring (Hera, Speak Pen). These tools reflect practical trade-offs: turnkey quality vs. customization, cloud streaming vs. local privacy, and SDKs for embedding capture/transcription/agents into apps. Why it matters now: distributed work, ubiquitous conferencing, and conversational agents have made accurate, low-latency audio processing a core infrastructure need. Developers increasingly choose SDKs that provide streaming transcripts, speaker labeling, and hooks for downstream analytics or voice agents. At the same time, open-source voice stacks and privacy-focused mobile capture broaden deployment options. Responsible use — consent, watermarking, and compliance with voice‑data regulations — is a central consideration when deploying cloning or transcription at scale. This topic helps teams select appropriate tools and architectures across voice synthesis, transcription, and conversation-intelligence workflows.