Modern product teams choose from a growing set of AI voice and speech recognition platforms to add transcription, text‑to‑speech (TTS), voice agents, and conversation intelligence into apps and contact centers. As of 2026, the market emphasizes low‑latency streaming APIs and SDKs, stronger privacy/compliance controls (HIPAA, enterprise data retention), and tighter integration between speech stacks and large language models for summarization and intent parsing. Key categories include Voice Synthesis and Transcription (high‑quality TTS and voice cloning), Text‑to‑Speech tools (multilingual voice generation and dubbing), Conversation Intelligence (speaker diarization, action‑item extraction, analytics), and AI Meeting Assistants (real‑time capture, summaries, and search). Representative platforms: ElevenLabs (expressive TTS, high‑fidelity voice cloning, and transcription); Murf AI (studio‑grade TTS, multilingual dubbing, and real‑time voice APIs); Fireflies (meeting capture, live transcription, summaries, and speaker labeling); Recall.ai (APIs/SDKs for capturing and surfacing meeting recordings and metadata across conferencing platforms); Krisp (noise cancellation, real‑time transcription, and audio quality features); OpenCall AI (HIPAA‑compliant phone and messaging automation for healthcare and sales); ZenCall.ai and Simple Phones (real‑time AI phone agents that route calls, book appointments, and integrate with CRMs). When selecting a provider, teams should weigh real‑time vs. batch needs, on‑prem or private‑cloud options, compliance requirements, transcription accuracy for domain vocabulary, cost per streaming minute, and controls around voice cloning and consent. The current trend favors composable stacks—pairing specialized speech SDKs with LLMs—to deliver concise meeting insights, robust voice UX, and auditable production deployments.