The model was fine-tuned on 25 hours of German VoxPopuli speech after simulating
G.711 A-law telephone audio. The goal is not to claim a new state of the art; it
is to show a practical, reproducible adaptation pass for a local voice stack
where narrowband/telephone audio is a common failure mode.
We built this checkpoint after seeing that German telephone-like audio was one
of the weaker conditions in our local voice pipeline. After fine-tuning, the
same evaluation setup showed a measurable improvement on held-out
telephony-style German audio, so we packaged the resulting NeMo artifact as a
reusable starting point for German phone-audio ASR experiments.
Model File
The fine-tuned NeMo artifact is:
nemotron-3.5-asr-de-telephony.nemo
What Changed
Starting from the NVIDIA Nemotron 3.5 ASR streaming 0.6B checkpoint, we fine-tuned
on German speech converted through this telephony degradation chain:
This keeps the model input at 16 kHz, while exposing the model to the bandwidth
and codec artifacts of 8 kHz A-law telephone audio.
In practical terms, this is a compact domain-adaptation run: the model remains
the same multilingual streaming ASR architecture, but its weights were adapted
toward the kind of German audio we expect in local telephony and voice-agent
workflows.
Training subset used here: 25.0 h exported from VoxPopuli German
Final split after telephony conversion:
Train: 8,431 utterances, 19.948 h
Validation: 1,054 utterances, 2.500 h
Test: 1,054 utterances, 2.552 h
Important limitation: VoxPopuli is parliamentary/broadcast-style speech, not real
call-center audio. The telephone condition here is simulated, not captured from
real PSTN or contact-center traffic.
Fine-Tuning Setup
Base model: nvidia/nemotron-3.5-asr-streaming-0.6b
Framework: NVIDIA NeMo
Precision: bf16-mixed
Epochs: 8
Batch size: 48
Optimizer: AdamW inherited from the base config
Learning rate: 5e-5
Scheduler: cosine, warmup_steps=500, min_lr=1e-6
Best checkpoint selected by validation WER
Best checkpoint: best-step=1264-val_wer=0.1168.ckpt
Final .nemo exported after restoring the best validation checkpoint
Evaluation
Evaluation was run on the held-out VoxPopuli German telephony-style test split
with German prompt conditioning and language-tag stripping enabled.
Model
Test set
WER
CER
Base nvidia/nemotron-3.5-asr-streaming-0.6b
1,054 utts
14.81%
7.82%
This fine-tuned model
1,054 utts
12.42%
6.86%
Absolute WER improvement: 2.39 percentage points.
Relative WER reduction: 16.1% fewer word errors compared with the base model
on this test split.
Intended Use
This model is intended as an experimental German ASR telephony adaptation and as
a starting point for further in-domain fine-tuning. It may be useful for:
local German voice-agent stacks with telephone-like audio
quick evaluation of G.711 A-law domain adaptation
follow-up fine-tuning on real call-center or telephony recordings
teams that want a concrete example of adapting a strong ASR base model to a
narrower audio domain
This checkpoint was packaged from a local fine-tuning run used to validate our
German telephone-audio pipeline. The included metrics are from the held-out
VoxPopuli telephony-style test split; users should still run their own
evaluation on their target audio before making product decisions.
Not Intended For
This model should not be presented as:
a state-of-the-art German ASR model
a validated production call-center ASR benchmark
a replacement for testing on real target-domain audio
Before production use, evaluate on real deployment audio, including different
speakers, microphones, noise conditions, and streaming chunk settings.
