iframe-proxy

pzelasko · 2025-06-04T15:37:04Z

What does this PR do ?

Adds tests and fixes inconsistency in ASR feature extractor and subsampling when processing the same input with and without padding. Specifically:

decreases feature extractor's sequence length tensor by 1 as the previously computed value included an extra padding frame in majority of the cases
removes a Dirac-delta-like spike due to lack of masking in preemphasis (only present when audio_length < audio.shape["time"])
replaces "reflect" padding with zero-padding for padding-length-invariance
replaces convolution with masked convolution in subsampling to discard frames outside of the sequence length

As a result, the models' WER outcomes vary much less with batch size, but the outcome is still not 100% identical across batch sizes. For example, for parakeet-tdt-0.6b-v2, parakeet-rnnt-1.1b, and canary-180m-flash the absolute difference between batch sizes 128 and 512 was 0.01% WER.

Comparison of all NVIDIA NeMo ASR models on Open ASR Leaderboard (offline only):

I also checked the results on NVTalks for one cache-aware model:

Model	Current WER	New WER	Relative diff
stt_en_fastconformer_hybrid_large_streaming_1040ms	14.73	14.75	0.13%

Collection: ASR

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Signed-off-by: Piotr Żelasko <petezor@gmail.com>

nithinraok

LGTM. Checked with parakeet models as well.

nithinraok · 2025-06-04T18:07:36Z

+@pytest.mark.skip(reason="Used only for debugging.")
+@pytest.mark.parametrize("length", [16000])
+def test_canary_invariant_to_padding(deterministic_rng, length):
+    model = ASRModel.from_pretrained("nvidia/canary-180m-flash").eval()


no pretrained :)

Signed-off-by: Piotr Żelasko <petezor@gmail.com>

…hub.com/nvidia/nemo into fix-pad-inconsistency-feature-extractor

Signed-off-by: Piotr Żelasko <petezor@gmail.com>

tango4j · 2025-06-27T18:40:04Z

Just commenting for future reference.
To make the code future-proof, For speaker diarization (Sortformer), I imported the featurizer's parameters and then use the same formula to calculate the total feature frame count.

For Sortformer, Lhotse-based inference is supported but training is not supported yet.
Will update this with the Streaming Sortformer updates (feature frame calculation etc)

Signed-off-by: taejinp <tango4j@gmail.com>

Signed-off-by: Piotr Żelasko <petezor@gmail.com>

github-actions · 2025-07-01T20:49:41Z

[🤖]: Hi @pzelasko 👋,

We wanted to let you know that a CICD pipeline for this PR just finished successfully.

So it might be time to merge this PR or get some approvals.

//cc @chtruong814 @ko3n1g @pablo-garay @thomasdhc

tango4j · 2025-07-01T21:11:20Z

nithinraok

Great work!

* Fix feature extractor to be invariant to padding Signed-off-by: Piotr Żelasko <petezor@gmail.com> * fix ci Signed-off-by: Piotr Żelasko <petezor@gmail.com> * preliminary conformer inference parity with/without padding Signed-off-by: Piotr Żelasko <petezor@gmail.com> * fix Signed-off-by: Piotr Żelasko <petezor@gmail.com> * fix tests Signed-off-by: Piotr Żelasko <petezor@gmail.com> * fixes Signed-off-by: Piotr Żelasko <petezor@gmail.com> * fix CI check Signed-off-by: Piotr Żelasko <petezor@gmail.com> * fix to cache-aware models Signed-off-by: Piotr Żelasko <petezor@gmail.com> * fix a bunch of tests Signed-off-by: Piotr Żelasko <petezor@gmail.com> * Fix failing CI tests Signed-off-by: Piotr Żelasko <petezor@gmail.com> * Fix failing CI tests part 2 Signed-off-by: Piotr Żelasko <petezor@gmail.com> * Unit test fixes for too short feature extractor inputs Signed-off-by: Piotr Żelasko <petezor@gmail.com> * Resolved feature frame length issue in E2E diarization dataloader Signed-off-by: taejinp <tango4j@gmail.com> * Apply isort and black reformatting Signed-off-by: tango4j <tango4j@users.noreply.github.com> * fix ci Signed-off-by: Piotr Żelasko <petezor@gmail.com> * removed test_ds from YAML file since it is not used Signed-off-by: taejinp <tango4j@gmail.com> * fix diarization unit tests after recent changes Signed-off-by: Piotr Żelasko <petezor@gmail.com> --------- Signed-off-by: Piotr Żelasko <petezor@gmail.com> Signed-off-by: taejinp <tango4j@gmail.com> Signed-off-by: tango4j <tango4j@users.noreply.github.com> Co-authored-by: oliver könig <okoenig@nvidia.com> Co-authored-by: Charlie Truong <chtruong@nvidia.com> Co-authored-by: taejinp <tango4j@gmail.com> Co-authored-by: tango4j <tango4j@users.noreply.github.com> Signed-off-by: Amir Hussein <amhussein@nvidia.com>

* Fix feature extractor to be invariant to padding Signed-off-by: Piotr Żelasko <petezor@gmail.com> * fix ci Signed-off-by: Piotr Żelasko <petezor@gmail.com> * preliminary conformer inference parity with/without padding Signed-off-by: Piotr Żelasko <petezor@gmail.com> * fix Signed-off-by: Piotr Żelasko <petezor@gmail.com> * fix tests Signed-off-by: Piotr Żelasko <petezor@gmail.com> * fixes Signed-off-by: Piotr Żelasko <petezor@gmail.com> * fix CI check Signed-off-by: Piotr Żelasko <petezor@gmail.com> * fix to cache-aware models Signed-off-by: Piotr Żelasko <petezor@gmail.com> * fix a bunch of tests Signed-off-by: Piotr Żelasko <petezor@gmail.com> * Fix failing CI tests Signed-off-by: Piotr Żelasko <petezor@gmail.com> * Fix failing CI tests part 2 Signed-off-by: Piotr Żelasko <petezor@gmail.com> * Unit test fixes for too short feature extractor inputs Signed-off-by: Piotr Żelasko <petezor@gmail.com> * Resolved feature frame length issue in E2E diarization dataloader Signed-off-by: taejinp <tango4j@gmail.com> * Apply isort and black reformatting Signed-off-by: tango4j <tango4j@users.noreply.github.com> * fix ci Signed-off-by: Piotr Żelasko <petezor@gmail.com> * removed test_ds from YAML file since it is not used Signed-off-by: taejinp <tango4j@gmail.com> * fix diarization unit tests after recent changes Signed-off-by: Piotr Żelasko <petezor@gmail.com> --------- Signed-off-by: Piotr Żelasko <petezor@gmail.com> Signed-off-by: taejinp <tango4j@gmail.com> Signed-off-by: tango4j <tango4j@users.noreply.github.com> Co-authored-by: oliver könig <okoenig@nvidia.com> Co-authored-by: Charlie Truong <chtruong@nvidia.com> Co-authored-by: taejinp <tango4j@gmail.com> Co-authored-by: tango4j <tango4j@users.noreply.github.com>

Fix feature extractor to be invariant to padding

517a297

Signed-off-by: Piotr Żelasko <petezor@gmail.com>

pzelasko requested review from VahidooX, nithinraok and titu1994 June 4, 2025 15:37

github-actions Bot added the ASR label Jun 4, 2025

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Comment thread tests/collections/asr/test_padding_and_batch_size_invariance.py Fixed

pzelasko added the Run CICD label Jun 4, 2025

Merge branch 'main' into fix-pad-inconsistency-feature-extractor

d27b873

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fix ci

8059734

Signed-off-by: Piotr Żelasko <petezor@gmail.com>

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Merge branch 'main' into fix-pad-inconsistency-feature-extractor

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pzelasko added 2 commits June 5, 2025 19:29

preliminary conformer inference parity with/without padding

5cd3bd7

Signed-off-by: Piotr Żelasko <petezor@gmail.com>

Merge branch 'fix-pad-inconsistency-feature-extractor' of https://git…

c314f43

…hub.com/nvidia/nemo into fix-pad-inconsistency-feature-extractor

pzelasko dismissed nithinraok’s stale review via c314f43 June 5, 2025 23:29

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fix

5cc82c9

Signed-off-by: Piotr Żelasko <petezor@gmail.com>

ko3n1g added Run CICD and removed Run CICD labels Jun 27, 2025

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fix ci

9f3ac5c

Signed-off-by: Piotr Żelasko <petezor@gmail.com>

pzelasko added the Run CICD label Jun 27, 2025

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removed test_ds from YAML file since it is not used

211eea8

Signed-off-by: taejinp <tango4j@gmail.com>

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fix diarization unit tests after recent changes

50d4fa7

Signed-off-by: Piotr Żelasko <petezor@gmail.com>

pzelasko added the Run CICD label Jul 1, 2025

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pzelasko merged commit 0fd4de5 into main Jul 2, 2025

pzelasko deleted the fix-pad-inconsistency-feature-extractor branch July 2, 2025 12:37

This was referenced Sep 7, 2026

ConvSubsampling forward broken: chunking=-1, striding_conv1d/dw_striding_conv1d, and vggnet all raise TypeError #16223

Open

fix(asr): repair ConvSubsampling forward paths missed by the MaskedConvSequential refactor #16225

Open

MahmoudAshraf97 mentioned this pull request Sep 19, 2026

Prepend Silence to Audio in Cache Aware Training #16273

Open

2 of 8 tasks

kzos mentioned this pull request Sep 20, 2026

fix(asr): use per-stream valid lengths for cache-aware streaming online normalization #16287

Open

5 of 7 tasks

Model	Current WER	New WER	Relative diff
CTC
nvidia/parakeet-ctc-1.1b	7.4	7.39	-0.14%
nvidia/parakeet-ctc-0.6b	7.69	7.65	-0.52%
nvidia/stt_en_fastconformer_ctc_large	8.96	8.94	-0.22%
nvidia/stt_en_conformer_ctc_large	8.32	8.5	2.16%
nvidia/stt_en_conformer_ctc_small	11.16	11.16	0.00%
RNNT
nvidia/parakeet-tdt-0.6b-v2	6.05	6.06	0.17%
nvidia/parakeet-tdt-1.1b	7.01	6.92	-1.28%
nvidia/parakeet-rnnt-1.1b	7.12	7.04	-1.12%
nvidia/parakeet-rnnt-0.6b	7.5	7.42	-1.07%
nvidia/stt_en_fastconformer_transducer_large	9.06	8.57	-5.41%
stt_en_conformer_transducer_small	10.26	9.75	-4.97%
nvidia/parakeet-tdt_ctc-110m	7.49	7.49	0.00%
AED
nvidia/canary-1b-flash	6.35	6.31	-0.63%
nvidia/canary-180m-flash	7.12	7.08	-0.56%
nvidia/canary-1b	6.5	6.47	-0.46%

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Improve ASR models' invariance to padding/batch size - #13827

Improve ASR models' invariance to padding/batch size#13827
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