Slovenian streaming ASR β€” Nemotron-3.5 fine-tune (v3)

nvidia/nemotron-3.5-asr-streaming-0.6b (FastConformer-CacheAware RNNT, 638M) fine-tuned for Slovenian on ARTUR (858 h) + Common Voice β€” a low-latency streaming model that works across read and spontaneous speech. Runs on GPU via NeMo or on CPU via parakeet.cpp (GGUF).

Results (WER, normalized, held-out)

Test set WER
Common Voice sl 25.07%
ARTUR multi-domain 23.42%
ARTUR parliamentary (spontaneous) 21.66%
FLEURS sl 33.07%

Comparison β€” vs yuriyvnv/parakeet-tdt-0.6b-slovenian

Different design goals; honest numbers (normalized WER):

Test set This model (streaming) parakeet-tdt-0.6b-slovenian (non-streaming)
FLEURS sl 33.07% 17.74%
Common Voice sl 25.07% 8.81%
ARTUR parliamentary (spontaneous) 21.66% not reported
  • parakeet-tdt is better on clean read speech β€” stronger non-streaming base (parakeet-tdt-0.6b-v3), trained on read data (Common Voice + synthetic TTS).
  • This model is a streaming (real-time, low-latency, CPU-deployable) model trained on 858 h ARTUR + Common Voice, so it stays robust on spontaneous/conversational speech (parliamentary ~22%) β€” a domain read-only models don't target. (CV test differs slightly: CV26 here vs CV17 there.)

Pick by use case: read-speech accuracy β†’ parakeet-tdt; real-time streaming + spontaneous speech β†’ this model.

Files

  • nemotron_sl.nemo β€” NeMo checkpoint (GPU inference / further fine-tuning)
  • asr_sl_v3.gguf (q8_0) β€” parakeet.cpp CPU inference

How to run

# CPU, streaming, via parakeet.cpp β€” use lang tag sl-SI, 16 kHz mono
parakeet-cli --model asr_sl_v3.gguf --lang sl-SI audio.wav
# GPU via NeMo
from nemo.collections.asr.models import ASRModel
m = ASRModel.restore_from("nemotron_sl.nemo")
m.transcribe(["audio.wav"])   # 16 kHz mono; manifest lang/target_lang = "sl-SI"

License & data provenance

Released CC BY-SA 4.0 (to honor the ARTUR ShareAlike terms).

Input License
Base nvidia/nemotron-3.5-asr-streaming-0.6b OpenMDW-1.1 (retain NOTICE)
ARTUR 1.0 (CLARIN.SI, 858 h) CC BY-SA 4.0 (attribution + ShareAlike)
Common Voice sl CC0

Credit CLARIN.SI (ARTUR: hdl.handle.net/11356/1776 audio, /11356/1772 transcriptions), NVIDIA, and Mozilla Common Voice.

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