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nvidia-speech-nim

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Use NVIDIA Speech NIM microservices for speech production and voice workflows, including self-hosted ASR/STT, TTS, text translation, speech-to-speech pipeline design, Riva Python client integration, deployment planning, GPU/runtime sizing, licensing/privacy review, and production QA for transcription, captioning, voice agents, localization, and synthetic voice output.

skills/providers/speech-and-voice/nvidia-speech-nim/SKILL.md

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# NVIDIA Speech NIM

Use this skill when an agent must plan or implement a speech workflow with NVIDIA Speech NIM microservices rather than a generic speech API. Treat NVIDIA Speech NIM as a deployable containerized speech stack: the application talks to independent ASR, TTS, and NMT NIM containers over HTTP, gRPC, or WebSocket APIs, and the agent remains responsible for model/profile choice, orchestration, rights checks, audio custody, and QA.

Facts in this skill were verified from official NVIDIA sources on 2026-07-10 unless noted otherwise.

## First classify the job

Separate the user's request into one or more speech capabilities:

- ASR/STT: audio to text for transcription, captions, subtitles, call analytics, meeting notes, voice-agent input, or speech-to-text translation where an ASR model supports translation.
- TTS: text to speech for narration, localized voice-over, conversational output, accessibility, kiosk/agent responses, or approved voice cloning.
- NMT: text translation between languages. NVIDIA's documented Speech NIM translation route is a separate NMT container, not hidden inside every ASR or TTS call.
- Speech-to-speech translation: a pipeline that chains ASR -> NMT -> TTS. Do not present it as a single monolithic Speech NIM unless the selected model/card explicitly exposes an end-to-end speech-to-speech endpoint.
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