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nemotron-speech

Routes NVIDIA Nemotron Speech (Riva) NIM tasks — deploys, runs, and tests ASR, TTS, and NMT NIMs on build.nvidia.com or self-hosted.

2,728stars318forksUpdated 7/30/2026

Security Assessment

Safe(93/100)
Security Score93/100

About nemotron-speech

The nemotron-speech skill is a single routing entry point for all NVIDIA Nemotron Speech (Riva) NIM workflows, covering automatic speech recognition (ASR), text-to-speech (TTS), and neural machine translation (NMT). It solves the problem of navigating NVIDIA's sprawling Riva tooling by acting as a thin routing surface that identifies a user's task type and loads only the relevant detailed reference file, keeping context tight through progressive disclosure. The skill notes that "Nemotron Speech" is a brand-only rename of what NVIDIA still documents as Riva, so all commands, images, gRPC APIs, and doc URLs continue to use the Riva name.

Its capabilities span cloud-hosted inference via build.nvidia.com, self-hosted Docker deployment, client-protocol selection for ASR (gRPC, HTTP, WebSocket), custom NeMo model deployment through the four-phase riva-build / riva-deploy pipeline, ASR pipeline tuning (VAD, diarization, language models), and prerequisite driver/Docker/NGC setup. Reference files cover model selection across Parakeet, Canary, Whisper, Nemotron ASR Streaming, and Magpie TTS, plus deployment-readiness and GPU compatibility checks. The skill is explicitly security-conscious: it instructs treating NVIDIA_API_KEY and NGC_API_KEY as secrets, using --password-stdin for Docker login, storing keys in a credential manager or chmod 600 file, and avoiding world-writable cache directories.

Target users are ML engineers and DevOps practitioners deploying NVIDIA speech models, whether via cloud NIM endpoints or self-hosted GPU infrastructure. Typical use cases include standing up an ASR/TTS/NMT NIM, building a custom fine-tuned ASR pipeline from a .nemo or .riva checkpoint, checking GPU/driver prerequisites, and choosing the right model family for a task.

FAQ

What speech tasks does this skill support?

ASR (speech-to-text), TTS (text-to-speech), and NMT (translation), across model families including Parakeet, Canary, Whisper, Nemotron ASR Streaming, and Magpie TTS, either cloud-hosted on build.nvidia.com or self-hosted via Docker.

What are the prerequisites for self-hosted deployment?

An NVIDIA AI Enterprise entitlement plus completed environment setup: NVIDIA drivers, Docker, the NVIDIA Container Toolkit, an exported NGC_API_KEY, and the Riva Python client. Cloud inference only needs the nvidia-riva-client pip package and a valid NVIDIA_API_KEY.

How are API keys handled?

The skill treats NVIDIA_API_KEY and NGC_API_KEY as secrets and instructs users never to print, commit, or log them, preferring --password-stdin for Docker login and storing keys in a credential manager or a chmod 600 env file.

Can I deploy a custom fine-tuned model?

Yes. It documents a four-phase pipeline: obtain a deployable .riva or fine-tuned .nemo file, build an RMIR with riva-build, deploy the model repository with riva-deploy, and launch the NIM. Per-model syntax should be verified against NVIDIA's live docs and riva-build --help.

Is the reference content authoritative for exact build flags?

No. The skill deliberately routes version-specific details (container images, nemo2riva config blocks, riva-build defaults) to NVIDIA's canonical docs, NGC catalog, and --help output rather than inferring them from the skill text.

All Files

15 files
evals/evals.json10.0 KB
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references/asr-custom.md14.6 KB
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references/pipelines.md16.3 KB
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SKILL.md9.2 KB
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BENCHMARK.md4.0 KB
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references/deployment-readiness-checks.md7.8 KB
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references/asr.md25.7 KB
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references/setup.md6.9 KB
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skill.oms.sig6.8 KB
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evals/EVAL.md1.2 KB
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references/model-selection.md18.8 KB
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scripts/main.py10.3 KB
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references/nmt.md14.9 KB
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skill-card.md3.9 KB
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references/tts.md16.4 KB
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Install nemotron-speech

Download and extract the skill files to your .claude/skills/ directory.

Quick Setup:

  1. Copy the skill folder to .claude/skills/
  2. Claude will automatically detect and use the skill

Repository

nvidia/skills