nemo-speech

n8n community node for NeMo-Speech.cpp — offline speech-to-text (ASR), speaker diarization, VAD, punctuation, inverse text normalization, and translation using NVIDIA models. Fully self-contained static binary.

Package Information

Released: this month
Downloads: 0 weekly / 0 monthly
Latest Version: 1.5.2
Author: Suneet Kumar

Available Nodes

Documentation generating…

NeMo Speech icon
NeMo Speech
Offline Speech to Text (ASR) and Text to Speech (TTS) using NeMo-Speech.cpp with NVIDIA models (Parakeet, Nemotron, MagpieTTS). Runs fully on CPU.

Documentation

n8n-nodes-nemo-speech

An n8n community node for NeMo Speech — offline speech-to-text, speaker
diarization, voice-activity detection, punctuation/capitalization, inverse text normalization, and
translation, powered by NeMo-Speech.cpp (NVIDIA's
lightweight C++ inference runtime) and the parakeet-tdt-0.6b-v3 model (Q8_0 GGUF, ~714 MB).

Runs fully on-device / offline on CPU. No API keys, no cloud, no GPU required.

Install into n8n

n8n add-nodes n8n-nodes-nemo-speech
# or, in a container:
docker exec -it <n8n> n8n nodes:install n8n-nodes-nemo-speech

On first run the node self-heals (no postinstall):

  1. downloads the static nemo-speech binary + ffmpeg to ~/.n8n/nemo-speech/bin/<platform>-<arch>/, and
  2. auto-downloads the default ASR model (parakeet-tdt-0.6b-v3.q8_0.gguf) to ~/.n8n/nemo-speech/models/ on first transcription.
  3. auto-downloads any enabled companion models (diarization, VAD, punctuation, ITN grammars, translation) to the same directory on first use.

No binary or model weights are shipped in the npm package. All are fetched once and cached
under n8n's standard data volume (~/.n8n), so they survive container/pod restarts.
To use local copies instead, set NEMO_SPEECH_PATH / FFMPEG_PATH, or point the relevant
"Model Path" field at a local .gguf/directory.

How it works

  1. The audio (MP3, FLAC, OGG, M4A, WAV, …) is converted to 16 kHz mono PCM16 WAV via the bundled static ffmpeg.
  2. nemo-speech transcribe <wav> --device cpu runs the NeMo-Speech.cpp runtime with the Q8_0 GGUF model.
  3. The transcript (plain text, JSON, SRT, or WebVTT) is returned as a JSON property.

The parakeet-tdt model runs in offline full-context mode and handles arbitrarily long audio
(podcasts, lectures, meetings) — the >34-min empty-transcript bug some whisper.cpp-based tools hit
is specific to that implementation, not the model.

Features

The static binary is built with NeMo-Speech.cpp's ASR core: speech recognition (ASR), speaker
diarization, VAD, punctuation/capitalization (PnC), inverse text normalization (ITN), and
translation (NMT). Models and companion assets are auto-downloaded from official sources on first use.

Capability Mode / Trigger Notes
Speech to Text (ASR) Operation: transcribe parakeet-tdt-0.6b-v3 (default), nemotron-3.5-asr-streaming-0.6b, or custom HF model.
Speaker diarization opt-in (diarize) Auto-downloads NVIDIA's Nemotron-3-Diarization model; tags each word with a 1-based speaker id (JSON output).
VAD masking / endpointing opt-in (vadMasking / vadBasedEou) Auto-downloads the official Silero VAD 6.2.3 model.
PnC (punctuation/casing) opt-in (pnc) Restores punctuation/casing for plain-text models (e.g. parakeet-ctc).
ITN (inverse text normalization) opt-in (itn) "twenty twenty four" → "2024".
Translation (NMT) opt-in (translateTo) Auto-downloads NVIDIA's Riva-Translate-4B-Instruct-v2 model (4.2 GB).

Node inputs

Input Maps to nemo-speech Description
Input = Binary / URL — Audio source: a binary property from a previous node, or a URL (wav/mp3/flac/ogg/m4a).
Binary Property — Name of the binary property holding the audio (default data).
Audio URL positional arg Used when Input = URL.
Output Format --format text, json, srt, vtt. JSON/SRT/VTT add word timestamps.
VAD Masking --vad-masking Enable VAD feature masking (auto-downloads the official Silero 6.2.3 GGUF).
Diarize --diarize Enable speaker diarization (auto-downloads Nemotron-3-Diarization).
Endpointing --endpointing Mid-stream end-of-utterance detection.
Enable ITN --itn-model-dir (when on) Off by default. Auto-downloads the official multi-language grammars on first use.
Enable PnC --pnc-model (when on) Off by default. Auto-downloads the official PnC BERT model on first use.
Translate To --translate-to Target language code (e.g. es, de, fr, zh). Enables translation (auto-downloads Riva-Translate-4B-Instruct-v2).
Write Text File — Also write a .txt (returned as a transcript binary property).
Options → ASR Model --model Select from supported models (Parakeet TDT 0.6B v3, Nemotron 3.5 ASR Streaming 0.6B, Nemotron Speech Streaming EN 0.6B, Parakeet CTC 1.1B) or Custom. Shows Hugging Face repo ID.
Options → Custom ASR Model --model Enter any Hugging Face repo ID (e.g. nvidia/parakeet-tdt-0.6b-v3) or local .gguf file path. Auto-downloads from HF.
Options → Device --device cpu, cuda:0, metal, vulkan:0. Default cpu.
Options → Stream Mode --stream Feed audio in 160 ms chunks through the streaming recognizer.
Options → Word Timestamps --word-times Include per-word timestamps (JSON).
Options → Verbose Logs --verbose Enable verbose diagnostics.
Options → Quiet --quiet Suppress all logging; only the transcript is returned.
Options → LM Path --lm-path KenLM .bin/.arpa for Flashlight beam search (requires a flashlight build).
Options → Lexicon Path --lexicon Flashlight lexicon TSV.
Options → Tokenizer Path --tokenizer SentencePiece tokenizer for OOV boosting.
Options → Beam Size --beam-size Flashlight beam width (default 32).
Options → Beam Threshold --beam-threshold Beam pruning threshold (default 20.0).
Options → LM Weight --lm-weight LM rescoring weight (default 0.8).
Options → Word Score --word-score Word insertion bonus (default 1.0).
Options → Max Boost --max-boost CTC max per-word boost (default 10.0).
Options → Chunk Size --chunk-sec CTC buffered window in seconds (default 0.16).
Options → Left/Right Padding --left-pad-sec / --right-pad-sec CTC context in seconds (default 1.92).
Options → VAD Model Path --vad-model Leave empty to auto-download the official Silero 6.2.3 GGUF when VAD masking/EOU is enabled.
Options → VAD-Based Endpointing --vad-based-eou Use the VAD timeline (instead of token-silence) for endpointing.
Options → VAD Onset/Offset/Pad --vad-onset / --vad-offset / --vad-pad-ms VAD thresholds and padding.
Options → Diarization Model --diar-model Select Nemotron-3-Diarization (default), Diar Streaming Sortformer 4spk-v2, or Custom. Shows Hugging Face repo ID.
Options → Custom Diar Model --diar-model Enter custom Hugging Face repo ID or local .gguf file path.
Options → Profanity List Path --profanity-list Path to a profanity filter file.
Options → ITN Model Dir --itn-model-dir Custom grammar directory; only used when Enable ITN is on.
Options → PnC Model --pnc-model NVIDIA PnC BERT Base EN (default) or Custom HF repo ID / local .gguf path.
Options → NMT Model --nmt-model Riva-Translate-4B-Instruct-v2 (default) or Custom HF repo ID / local .gguf path.
Options → Speech Context --speech-context Comma-separated words to boost in the transcript.
Options → Output File Base Path — Base path for the .txt output; only used when Write Text File is on.

Every nemo-speech transcribe flag is exposed as a node input.

Output

Each input item produces one output item:

{
  "json": {
    "text": "And so, my fellow Americans, ask not what your country can do for you, ask what you can do for your country.",
    "model": "parakeet-tdt-0.6b-v3 (default)",
    "input": "data"
  }
}

With Diarize + Output Format = JSON, each word in text (parsed as JSON) carries a
1-based speaker field. With Write Text File enabled, a transcript binary property (the
.txt) is also attached.

Companion models (auto-downloaded)

All converted from official sources and hosted at
suneetk/nemo-speech-companions on
Hugging Face. Downloaded once, cached under ~/.n8n/nemo-speech/models/.

Companion Source Size
Diarization nvidia/Nemotron-3-Diarization (official HF repo GGUF) 107 MB
VAD snakers4/silero-vad v6.2.3 (official pip package, converted) 1.2 MB
PnC NVIDIA's punctuation_en_bert.nemo (NGC, converted) 139 MB
ITN grammars NeMo-Speech.cpp's official itn_configs.tar.bz2 release asset (Sparrowhawk, multi-language) 2.3 MB
Translation nvidia/Riva-Translate-4B-Instruct-v2 (official HF repo, converted to Q8_0 GGUF) 4.2 GB

Environment variables

Variable Purpose
NEMO_SPEECH_PATH Use this exact nemo-speech binary; skips the auto-download.
FFMPEG_PATH Use this exact ffmpeg binary; skips the auto-download.
NEMO_SPEECH_MODEL_DIR Override the model cache directory (default ~/.n8n/nemo-speech/models).

Binary (runtime download)

The npm package contains no binaries or weights. On first run the node downloads the static
nemo-speech binary (14 MB) + static ffmpeg (80 MB, from johnvansickle.com's static build)
from a GitHub Release asset, extracted to ~/.n8n/nemo-speech/bin/<platform>-<arch>/. Both
binaries are fully static (zero shared-lib dependencies), so they run on both glibc and musl
(Alpine) targets.

The static binary is built from NVIDIA/NeMo-Speech.cpp source by
.github/workflows/build-and-publish.yml (a new GitHub Release is cut per tag). Two small patches
in patches/ adapt the upstream build for a fully static (musl-compatible) binary:
static-itn-build.patch builds OpenFST/Sparrowhawk as static archives instead of shared libs, and
static-itn-link.patch links the ITN target against those archives with the linker flags needed
for OpenFST's static type-registration to work (--whole-archive) plus protobuf/re2/absl/zlib.

Build from source

npm install --ignore-scripts   # n8n-workflow pulls a native dep that needs no build here
npm run build                  # tsc -> dist/nodes/NemoSpeech/NemoSpeech.node.js
node smoke.test.js             # end-to-end smoke test (needs model + jfk.wav)

License

MIT. The nemo-speech binary is subject to the NeMo-Speech.cpp license (Apache-2.0).
The Parakeet ASR model is subject to the CC-BY-4.0 license. Companion models retain their
respective upstream licenses (NVIDIA Open Model License for Nemotron-3-Diarization, PnC, and
Riva-Translate; MIT for Silero VAD).

Discussion