[dashidhy]

Problems reproduced

While comparing cache-aware Nemotron streaming with our existing transcribe.cpp setup, we found audible speech missing from NeMo-Speech.cpp's output. Two separate issues contributed to these failures.

Rechecked on 2026-10-24 against main 2bdfb03: both the startup padding / unconditional first-chunk crop and the Q8 pointwise policy are still present. This PR is updated on top of that main revision.

1. Incorrect startup alignment

The first chunk has no previous audio chunk, but the runner prepends zero Mel history and the encoder applies the overlap crop intended for subsequent chunks. At R13, this encodes 9 zero frames + 112 real frames and drops two encoder frames, instead of starting with 105 real Mel frames and no overlap crop. This changes the initial encoder alignment/state; our earlier continuous-speech reproduction also showed a later blank-only interval that disappeared after correcting startup.

Fix: use 1 + subsampling_factor * R real Mel frames for the first chunk, without the extra prefix or overlap crop. Keep the existing 9-frame history and steady-state geometry. Cover R0, short EOF and reset. The update to current main preserves its newer EOU behavior: publishing a final does not reset acoustic/predictor state or restart first-chunk geometry.

2. Speech omitted after Q8 pointwise-convolution conversion

Even with startup corrected, a separate recording lost a speaker's job introduction in the middle of continuous speech. The same input retained that passage in the reference setup. Comparing the conversions showed that NeMo-Speech.cpp quantizes Conformer pointwise convolutions as linear layers, whereas the reference keeps them in F16 in its Q8 preset.

The reference is transcribe.cpp@8c7ae674: it separates ConvPw from other linear matrices. The change below follows that precision choice; it does not replace the decoder or attempt bit-exact parity with the entire reference runtime.

Fix: retain pointwise-convolution weights in F16 specifically for cache-aware RNNT Q8_0 exports. Other tensor classes, head/model types and requested weight types retain their existing policy. No new runtime precision modes or decoder-backend changes are introduced.

Existing GGUFs must be regenerated from the original checkpoint. Updating the runtime alone cannot repair previously quantized weights; casting old Q8 values to F16 cannot restore lost precision. The tested model grows by 67.5 MiB.

Before/after validation

Retested against main 2bdfb03 on an M2 Pro, Release/Metal build, with ASR, diarization and tests enabled; TTS and microphone capture disabled.

For the precision ablation, the same runtime processed 17 adjacent starting points, 20 ms apart, each with 120 seconds of the same recording (Auto/R3, Metal, no EOU/VAD, dynamic batching disabled):

Weights	Target introduction missing
Original NVIDIA Q8	1/17
Only pointwise weights restored to source F16 values	0/17

Only 48 tensors changed; the other 609 are byte-identical. All 48 F16 tensors were checked against the corresponding original high-precision checkpoint values. These are correlated windows from one recording, not an independent corpus or a WER/CER improvement claim. They do not establish that every omission is fixed.

• CTest: 13/13 passed, including model-backed geometry checks when NEMO_SPEECH_TEST_CACHE_AWARE_RNNT_MODEL is set at configure time. The model-free geometry invocation also passed; it explicitly reports that model checks were skipped. The separate variable leaves existing CTC-model test configurations unaffected.
• Converter contract tests: 20/20 passed, including an actual small synthetic-checkpoint GGUF export. The two critical new tests fail under the old conversion policy.
• Original and pointwise-F16 models: CPU/Metal first/history geometry, R0/R3/R6/R13, reset, packetized EOF and EOU checks passed.
• Pointwise-F16 model: JFK concurrency passed on CPU and Metal, 4 threads × 2 iterations.
• Full-model runtime A/B used a controlled GGUF copy changing only those 48 tensors; this is distinct from the synthetic end-to-end converter regression.

CUDA/Vulkan and broader-corpus quality were not tested. The earlier reported Metal concurrency failures on another local recording are not claimed fixed. The converter tests ran with a canonical temporary directory and without a system llama-quantize on the test PATH, avoiding unrelated S2S test-environment dependencies. Formatting/conflict/size hooks pass; the global license-header hook still flags unchanged upstream src/runtime/ggml/llama_log_shim.cpp because the checker also requires a parakeet-derived notice for that directory. That unrelated file/rule is not changed here.

Build and regression commands

# Optional: export NEMO_SPEECH_TEST_CACHE_AWARE_RNNT_MODEL=/absolute/path/to/MODEL.gguf before configure.
scripts/configure.sh metal-asr -DNEMO_SPEECH_BUILD_TESTS=ON -DNEMO_SPEECH_BUILD_MIC_CAPTURE=OFF
cmake --build --preset metal-asr --parallel 3
ctest --test-dir build/metal-asr --output-on-failure
python -m unittest discover -s tests/conversion -p converter_contract_test.py
build/metal-asr/bin/test_cache_stream_geometry MODEL.gguf --gpu -1
build/metal-asr/bin/test_cache_stream_geometry MODEL.gguf --gpu 0
build/metal-asr/bin/test_rnnt_concurrency MODEL.gguf test_files/asr/wav/test/jfk.wav \
  --gpu 0 --threads 4 --iters 2 --right-context 13 --language auto
# The concurrency check was also run with --gpu -1.

Scope and provenance

The PR remains limited to streaming startup, the targeted conversion policy, direct regression tests and the reconversion note. No general precision framework, application code, audio, transcripts, models or experiment logs are included. Tests generate their own fixtures. Commits are DCO-signed and existing notices are preserved.

Local weight controls use NVIDIA's published GGUF and high-precision checkpoint under OpenMDW 1.1. Earlier startup validation used BAAI/CS-Dialogue, CC-BY-NC-SA-4.0; none of that data is part of the patch.

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Reviewing files that changed from the base of the PR and between a0f3e14 and c4d76ed.

Files selected for processing: 4

• src/asr/encoder/fastconformer.h
• src/asr/runner.cpp
• tests/cpp/asr/test_cache_stream_geometry.cpp
• tests/cpp/asr/test_endpointer.cpp

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📝 Summary

Summary by CodeRabbit

• Bug Fixes

  • Corrected context handling for the first audio chunk while preserving overlap handling for later chunks.
  • Improved consistency across chunk sizes, end-of-stream processing, endpoint timing, and resets.
  • Cache-aware RNNT exports using Q8_0 retain pointwise convolution weights in F16.

• Documentation

  • Clarified cache-aware RNNT export precision behavior and noted that existing quantized exports must be regenerated from the original checkpoint to apply it.

• Tests

  • Added coverage for streaming geometry, output consistency, reset behavior, end-of-stream handling, endpoint timing, and optional model execution.

The cache-aware encoder and runner now use separate first-chunk and steady-state chunk geometry. The runner manages overlap, startup history, finalization, and resets, and computes decoded-mel timing from emitted frames. Cache-aware RNNT conversion selects F16 for pointwise convolution weights when the linear quantization type is Q8_0.

Changes: Cache-aware stream geometry

Layer / File(s)	Summary
Chunk geometry contracts src/asr/encoder/cache_aware_encoder.h, src/asr/encoder/fastconformer.h, src/asr/runner.h	Documentation and EncoderConfig helpers define first-chunk and subsequent-chunk geometry, plus decoded-mel frontier calculation. CacheStreamRunner tracks first_chunk_ and declares next_chunk_mel_frames().
First-chunk and steady-state processing src/asr/encoder/fastconformer.cpp, src/asr/runner.cpp	The encoder skips extra-frame trimming for the first chunk. The runner selects chunk sizes based on startup state, handles initial history and overlap, updates decoded-mel timing, and uses startup-aware sizing during finalization.
Geometry and streaming validation tests/cpp/asr/CMakeLists.txt, tests/cpp/asr/test_cache_stream_geometry.cpp, tests/cpp/asr/test_endpointer.cpp	Tests check chunk geometry, encoder output, packetization, finalization, forced EOU, reset behavior, and VAD endpoint timing.

Cache-aware RNNT Q8 precision

Layer / File(s)	Summary
Pointwise convolution precision policy conversion/asr.py, tests/conversion/converter_contract_test.py, docs/model-conversion.md	Cache-aware RNNT conversion selects F16 for pointwise convolution weights when the linear quantization type is Q8_0. Tests check dtype selection and exported values. Documentation describes the exception and how it applies to existing GGUFs.

Priority: Normal

Estimated code review effort: 3 (Moderate) | ~25 minutes

Change: Bug fix

Possibly related issues

• Arabic streaming RNNT drops words with Q4 and FP16 #71: The issue reports dropped words in streaming RNNT. This PR changes first-chunk alignment and cache-aware Q8 pointwise-weight precision, but the issue notes that higher weight precision alone did not resolve its mid-stream case.

Merge Risk: Minimal · up to c4d76

The streaming timing correction is in place, and the examined tests cover the questioned boundary and reset behavior. No identified issue prevents merging after normal checks.

Pre-merge checks: 4 · 1

Failed checks: 1 warning

Check name	Status	Explanation	Resolution
Docstring Coverage		Docstring coverage is 13.79% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 29 functions across 9 files.	Write docstrings for the functions missing them to satisfy the coverage threshold.

Passed checks: 4 passed

Check name	Status	Explanation
Title check		The title names the two changes in the PR: streaming startup correction for cache-aware RNNT, and Q8 pointwise-convolution precision. The raw summary confirms the runner, encoder, and conversion chang…
Description check		The description explains the two reported problems: incorrect first-chunk startup padding/cropping and Q8 pointwise-convolution quantization. It also gives the fixes, validation results, and the need …
Linked Issues check		Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check		Check skipped because no linked issues were found for this pull request.

Full details: Title check

Explanation

The title names the two changes in the PR: streaming startup correction for cache-aware RNNT, and Q8 pointwise-convolution precision. The raw summary confirms the runner, encoder, and conversion changes that match both halves of the title.

Full details: Description check

Explanation

The description explains the two reported problems: incorrect first-chunk startup padding/cropping and Q8 pointwise-convolution quantization. It also gives the fixes, validation results, and the need to regenerate GGUFs. These all match the changeset.

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[VitorAMJorge]

I have tested the idea with a small curated dataset in pt-BR and en, trimming initial silence and it halves the number of lost words at the start of the stream.

[greptile-apps]

Confidence Score: 5/5

[Medium impact] The PR appears safe to merge; no new actionable issues were found.

Summary

Corrects cache-aware RNNT startup and keeps pointwise convolution weights in F16 for Q8_0 exports.

• Cache-aware RNNT streams start with the real beginning of the audio.
• Cache-aware RNNT Q8 exports keep pointwise weights in F16.

_{Reviews (4) · Last reviewed commit: "fix(asr): align VAD endpoint clock with ..." · Reviewed by Greptile}

[coderabbitai]

🧹 Nitpick comments: 1

tests/cpp/asr/CMakeLists.txt: 1

13-15: 📐 Maintainability & Code Quality | 🔵 Trivial | ⚡ Quick win

Register the model-backed check when a test model is available.

The current CTest command runs only check_shapes(). The encoder/runner comparisons in check_model() run only when main receives a model path, so the changed first-chunk behavior is not covered by the registered test. Add an opt-in model-backed CTest case using the existing NEMO_SPEECH_TEST_ASR_MODEL convention.

Suggested fix

 add_executable(test_cache_stream_geometry test_cache_stream_geometry.cpp)
 target_link_libraries(test_cache_stream_geometry PRIVATE nemo_speech_asr)
 add_test(NAME cache_stream_geometry COMMAND test_cache_stream_geometry)
+if(DEFINED ENV{NEMO_SPEECH_TEST_ASR_MODEL} AND
+   NOT "$ENV{NEMO_SPEECH_TEST_ASR_MODEL}" STREQUAL "")
+    add_test(
+        NAME cache_stream_geometry_model
+        COMMAND test_cache_stream_geometry $ENV{NEMO_SPEECH_TEST_ASR_MODEL})
+endif()

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Review comment at @tests/cpp/asr/CMakeLists.txt around lines 13 - 15:
Add an opt-in model-backed CTest case alongside the existing
cache_stream_geometry test in the test registration section. When
NEMO_SPEECH_TEST_ASR_MODEL is defined and non-empty, register
test_cache_stream_geometry with that model path so its check_model() comparisons
run; leave the shape-only test unchanged.

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Nitpick comments:
Review comments at @tests/cpp/asr/CMakeLists.txt:
- Around line 13-15: Add an opt-in model-backed CTest case alongside the
existing cache_stream_geometry test in the test registration section. When
NEMO_SPEECH_TEST_ASR_MODEL is defined and non-empty, register
test_cache_stream_geometry with that model path so its check_model() comparisons
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[dashidhy]

@pskrunner14 @anand-nv @rmittal-github I'll appreciate it if you guys could take a moment to help on this. The PR has been here for over a month and it seems that my issues are still not fixed in the main branch.

[pskrunner14]

/ok to test a0f3e14

[pskrunner14]

@dashidhy apologies this took a while, thanks for sticking with it. This is a critical fix, both issues directly lose words in the default format we use.

Added one comment on src/asr/runner.cpp:956 (minor: the VAD endpoint clock is ~70 ms ahead after the geometry change).

[pskrunner14]

LGTM. Thanks @dashidhy!

[dashidhy]

@pskrunner14 Thanks for reviewing and merging this PR

Your VAD clock comment prompted me to audit the broader timestamp path, since padding can affect more than my application's use case. I found two additional issues that seem worth discussing as a follow-up. I have not submitted further code changes for these findings.

First, EOF padding can produce word timestamps beyond the actual audio duration. With the first 0.64 seconds of the repository's JFK sample at R13, the SDK and CLI return:

Audio duration: 0.64s
"And": 1.12–1.20s
"so":  1.68–1.76s

The SRT output carries the same out-of-range timestamps, and these word times also feed speaker attribution. I reproduced the overrun on CPU and Metal with both the current and pre-PR runner logic using the same weights, so it appears to be pre-existing, rather than introduced by this PR. The apparent mechanism is that EOS padding advances the decoder's frame positions, which are then exported as word times without an audio-duration bound. Simply clamping them would not necessarily recover meaningful word alignment.

Second, audio_processed has different meanings across runners: the cache-aware RNNT path reports received audio duration, while the buffered CTC path reports its decode/emit cursor.

Before implementing a follow-up, could you advise on the intended contracts?

• Should word timestamps represent nominal decoder emission positions, or must they always lie within the actual audio? How should words emitted during EOS padding be timed while preserving their text?
• Should audio_processed represent received audio or decoded progress?
• Would you prefer a separate issue/PR for these findings, or would maintainers prefer to handle the changes given the shared API and diarization implications?

I can provide the minimal reproducer and regression tests. I would like to agree on the intended behavior before changing timestamp semantics across the stack.

[pskrunner14]

@dashidhy thanks for digging into this, these are really good findings. Answering your questions below:

Word timestamps: they should always fall within the actual audio. RNNT word times are emission positions, which NeMo uses too: the token's emission frame (greedy, label-looping) times window_stride * subsampling_factor (offsets, seconds). The difference is that NeMo never decodes past real audio: the decoder is bounded by encoder_output_length (here), and the tail-chunk padding is excluded from the lengths (here). Our finalize() deliberately decodes into zero padding to flush pending tail tokens, which is where the overrun comes from.

One clean option is to keep that flush but clamp at the source: record the last encoder frame covering real audio before the EOS pad (with causal geometry, (M - 1) / sub + 1 for M real mel frames), and clamp start_frame/end_frame to it, keeping order and end > start. Words emitted in the padding keep their text and land on the last real frame(s), which matches where NeMo would have to emit them. Doing it in the runner/decoder means SRT, ITN alignment and diarization all inherit the bound. If you find dropping the padding NeMo-style doesn't lose tail words, that would be simpler, but I'd verify that first.

audio_processed: it should be decoded progress. The cache-aware runner should match the CTC path.

Follow-up: a separate issue/PR from you would be great, since you provided the analysis and repro. Please include the 0.64 s JFK/R13 case as a regression test asserting every word ends within the audio duration.

[dashidhy]

@pskrunner14 Thanks for the guidance. After a closer review, the two additional findings—EOF word timestamps extending beyond the recording and the inconsistent meaning of audio_processed—appear to be pre-existing issues rather than regressions introduced by #46. The approximately 70 ms VAD clock mismatch raised during review was already addressed before #46 was merged.

My current application does not exercise the affected downstream paths sufficiently to validate broader changes to timestamp semantics and their consequences. I’ve therefore closed #78 and am not proposing further behavioral changes for these findings at this point.

The reproducer and observations above remain available for reference. I’ll leave further investigation and decisions about the intended behavior to the maintainer team. I wanted to clarify that these findings should be considered separately from the first-chunk fix in #46, rather than treated as unresolved consequences of that change. Thanks!