Add NeMo Conformer CTC aligner ONNX v1

README.md

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+---
+library_name: onnxruntime
+pipeline_tag: automatic-speech-recognition
+tags:
+- onnx
+- ctc
+- forced-alignment
+- word-timestamps
+- mobile
+- flutter
+---
+
+# Fluency NeMo Conformer CTC Aligner
+
+This repository contains the mobile-distribution assets for Fluency's English word-level forced alignment pipeline.
+
+The model is not used as a standalone ASR decoder in the app. Whisper provides the transcript, this model provides frame-level CTC log-probabilities, and the app runs constrained CTC Viterbi to recover word timestamps.
+
+## Runtime Pipeline
+
+```text
+Whisper transcript
+→ text normalization
+→ SentencePiece tokenizer
+→ native log-mel feature extraction
+→ ONNX Runtime Mobile
+→ constrained CTC Viterbi
+→ word timestamps
+```
+
+## Required App Assets
+
+```text
+stt_en_conformer_ctc_small_features.onnx
+metadata.json
+tokenizer/tokenizer.model
+tokenizer/vocab.txt
+manifest.json
+```
+
+Optional debugging assets are under `parity/`.
+
+## ONNX Contract
+
+- Input `processed_signal`: `[batch, 80, feature_frames]` float32
+- Input `processed_signal_length`: `[batch]` int64
+- Output `log_probs`: `[batch, encoded_frames, 1025]` float32
+- Output `encoded_len`: `[batch]` int64
+- CTC blank id: `1024`
+
+## Feature Contract
+
+- Sample rate: `16000 Hz`
+- Channels: mono
+- Feature type: 80-bin log-mel spectrogram
+- Window size: `25 ms`
+- Window stride: `10 ms`
+- FFT: `512`
+- Window: Hann
+- Normalization: `per_feature`
+
+The ONNX graph intentionally starts after feature extraction. Mobile clients must implement NeMo-compatible log-mel features before invoking ONNX Runtime.
+
+## Validation
+
+Validated on a 375.838s video using raw Whisper `text` fields only:
+
+- Windows checked: 7
+- Segments checked: 110
+- Matched words checked: 1029
+- PyTorch feature+model total: 3.106s
+- ONNX model total: 5.396s
+- Log-prob mean abs diff: 0.000014
+- Word center delta p50/p95/max: 0.0ms / 0.0ms / 0.0ms
+
+See `parity/parity_1gzKSyOBpZg.json` and `parity/parity_1gzKSyOBpZg.csv` for details.
+
+## Download URLs
+
+```text
+https://huggingface.co/iamzhangship/fluency-nemo-conformer-ctc-aligner/resolve/main/stt_en_conformer_ctc_small_features.onnx
+https://huggingface.co/iamzhangship/fluency-nemo-conformer-ctc-aligner/resolve/main/metadata.json
+https://huggingface.co/iamzhangship/fluency-nemo-conformer-ctc-aligner/resolve/main/tokenizer/tokenizer.model
+https://huggingface.co/iamzhangship/fluency-nemo-conformer-ctc-aligner/resolve/main/tokenizer/vocab.txt
+https://huggingface.co/iamzhangship/fluency-nemo-conformer-ctc-aligner/resolve/main/manifest.json
+```
+
+## Checksums
+
+- ONNX sha256: `8998fd44bc2374c7d085f7c709fbfbd28ea6db09998622077071faf478db24fd`
+- ONNX size: `53197388` bytes
+
+Use `manifest.json` for full file sizes and sha256 checksums.
+
+## Source Model
+
+- NeMo pretrained model: `stt_en_conformer_ctc_small`
+- Export graph: Conformer encoder + CTC projection/log-softmax
+- Export metadata model bytes: `53197388`

manifest.json

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+{
+  "repoId": "iamzhangship/fluency-nemo-conformer-ctc-aligner",
+  "createdAt": "2026-07-07T01:35:00.724077+00:00",
+  "version": "v1",
+  "modelId": "nemo-conformer-ctc-small-aligner",
+  "runtime": "onnxruntime",
+  "requiredAssets": [
+    "stt_en_conformer_ctc_small_features.onnx",
+    "metadata.json",
+    "tokenizer/tokenizer.model",
+    "tokenizer/vocab.txt"
+  ],
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+      "mirrorUrl": "https://hf-mirror.com/iamzhangship/fluency-nemo-conformer-ctc-aligner/resolve/main/README.md"
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+      "mirrorUrl": "https://hf-mirror.com/iamzhangship/fluency-nemo-conformer-ctc-aligner/resolve/main/tokenizer/tokenizer.model"
+    },
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+      "url": "https://huggingface.co/iamzhangship/fluency-nemo-conformer-ctc-aligner/resolve/main/tokenizer/tokenizer.vocab",
+      "mirrorUrl": "https://hf-mirror.com/iamzhangship/fluency-nemo-conformer-ctc-aligner/resolve/main/tokenizer/tokenizer.vocab"
+    },
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+    }
+  }
+}

metadata.json

@@ -0,0 +1,87 @@
+{
+  "model": {
+    "name": "stt_en_conformer_ctc_small",
+    "source": "NVIDIA NeMo EncDecCTCModelBPE",
+    "onnx": "exports/models/stt_en_conformer_ctc_small_onnx/stt_en_conformer_ctc_small_features.onnx",
+    "onnxBytes": 53197388,
+    "opset": 17,
+    "dummyFeatureFrames": 6000
+  },
+  "audio": {
+    "sampleRate": 16000,
+    "channels": 1,
+    "sampleFormat": "float32 PCM in [-1, 1]"
+  },
+  "features": {
+    "type": "log-mel-spectrogram",
+    "features": 80,
+    "normalize": "per_feature",
+    "windowSizeSeconds": 0.025,
+    "windowStrideSeconds": 0.01,
+    "window": "hann",
+    "nFft": 512,
+    "log": true,
+    "frameSplicing": 1,
+    "dither": 1e-05,
+    "padTo": 0,
+    "padValue": 0.0
+  },
+  "ctc": {
+    "tokenizer": "SentencePiece",
+    "tokenCountWithoutBlank": 1024,
+    "tokenCountWithBlank": 1025,
+    "blankId": 1024,
+    "featureFrameStrideSeconds": 0.01,
+    "encoderSubsampling": 4,
+    "approxLogitFrameStrideSeconds": 0.04
+  },
+  "onnxContract": {
+    "inputs": [
+      {
+        "name": "processed_signal",
+        "shape": [
+          "batch",
+          80,
+          "feature_frames"
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "processed_signal_length",
+        "shape": [
+          "batch"
+        ],
+        "dtype": "int64"
+      }
+    ],
+    "outputs": [
+      {
+        "name": "log_probs",
+        "shape": [
+          "batch",
+          "encoded_frames",
+          1025
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "encoded_len",
+        "shape": [
+          "batch"
+        ],
+        "dtype": "int64"
+      }
+    ]
+  },
+  "tokenizerAssets": {
+    "vocab.txt": "exports/models/stt_en_conformer_ctc_small_onnx/tokenizer/vocab.txt",
+    "tokenizer.model": "exports/models/stt_en_conformer_ctc_small_onnx/tokenizer/tokenizer.model",
+    "tokenizer.vocab": "exports/models/stt_en_conformer_ctc_small_onnx/tokenizer/tokenizer.vocab",
+    "model_config.yaml": "exports/models/stt_en_conformer_ctc_small_onnx/tokenizer/model_config.yaml"
+  },
+  "mobileRuntimeNotes": [
+    "Compute features with the exact parameters above before calling ONNX.",
+    "Use the exported SentencePiece tokenizer; do not build a custom a-z tokenizer.",
+    "Run constrained CTC Viterbi in native code; do not use beam search for known transcript alignment."
+  ]
+}

parity/parity_1gzKSyOBpZg.csv

@@ -0,0 +1,118 @@
+kind,windowIndex,subtitleIndex,status,pytorchSeconds,onnxSeconds,maxAbsDiff,meanAbsDiff,encodedLenPyTorch,encodedLenOnnx,centerDeltaMs,text
+window,0,,matched,0.605,0.945,0.003302,1.3e-05,1501,1501,,
+segment,0,0,skipped_no_alignable_words / skipped_no_alignable_words,,,,,,,, [MUSIC PLAYING]
+segment,0,1,skipped_no_alignable_words / skipped_no_alignable_words,,,,,,,, [MUSIC PLAYING]
+segment,0,2,skipped_no_alignable_words / skipped_no_alignable_words,,,,,,,, [MUSIC PLAYING]
+segment,0,3,skipped_no_alignable_words / skipped_no_alignable_words,,,,,,,, [MUSIC PLAYING]
+segment,0,4,skipped_no_alignable_words / skipped_no_alignable_words,,,,,,,, [MUSIC PLAYING]
+segment,0,5,aligned / aligned,,,,,,,0.0, There is a magma chamber of anger
+segment,0,6,aligned / aligned,,,,,,,0.0, sat underneath British society right now.
+segment,0,7,skipped_no_alignable_words / skipped_no_alignable_words,,,,,,,, [MUSIC PLAYING]
+segment,0,8,aligned / aligned,,,,,,,0.0, Britain's been shifting to the right.
+segment,0,9,aligned / aligned,,,,,,,0.0, I've spent the past few months trying
+segment,0,10,aligned / aligned,,,,,,,0.0, to understand what's happening in this country.
+segment,0,11,aligned / aligned,,,,,,,0.0, No one speaks to the media law.
+segment,0,12,aligned / aligned,,,,,,,0.0," Attending far-right protests, including United Kingdom,"
+segment,0,13,aligned / aligned,,,,,,,0.0, one of the biggest far-right rallies ever
+segment,0,14,aligned / aligned,,,,,,,0.0," on the streets of the UK, where tens of thousands responded"
+segment,0,15,aligned / aligned,,,,,,,0.0, to the call at this man.
+segment,0,16,aligned / aligned,,,,,,,0.0," Anti-Islam activist Tommy Robinson,"
+segment,0,17,aligned / aligned,,,,,,,0.0, a convicted criminal turned anti-establishment figure.
+segment,0,18,aligned / aligned,,,,,,,0.0, Are you ready for the battle of Britain?
+segment,0,19,skipped_no_alignable_words / skipped_no_alignable_words,,,,,,,, [CHEERING]
+segment,0,20,aligned / aligned,,,,,,,0.0," But it's not just on the streets,"
+segment,0,21,aligned / aligned,,,,,,,0.0, and it's not just the extreme right that's on the up.
+segment,0,22,aligned / aligned,,,,,,,0.0, The populist right-wing party reform UK led by longtime Trump
+segment,0,23,aligned / aligned,,,,,,,0.0, online.
+window,1,,matched,0.513,0.886,0.000738,1.4e-05,1501,1501,,
+segment,1,24,aligned / aligned,,,,,,,0.0, The former U.K. led by longtime Trump ally Nigel Farage made massive gains in local elections in May.
+segment,1,25,aligned / aligned,,,,,,,0.0, This right word shift isn't one single movement.
+segment,1,26,aligned / aligned,,,,,,,0.0," The different groups represent different shades of right-wing politics,"
+segment,1,27,aligned / aligned,,,,,,,0.0, but they all seem to be feeding off of a divided Britain.
+segment,1,28,aligned / aligned,,,,,,,0.0, And the heart of those divisions is the issue of migration.
+segment,1,29,aligned / aligned,,,,,,,0.0," Just this week, a horrific attack by a Sudanese refugee on the streets of Belfast almost immediately turned into the latest ""I told you so"" moment for the far right."
+segment,1,30,aligned / aligned,,,,,,,0.0," Transforming a local tragedy into a national rallying cry, powerful allies, amplifying the message and fanning the flames of hate."
+segment,1,31,aligned / aligned,,,,,,,0.0," People in Britain are angry. Joe Mulhol infiltrated far-right groups, undercover here in the U.K. and in the U.S."
+segment,1,32,aligned / aligned,,,,,,,0.0, He's one of the U.K.'s top experts on these movements.
+segment,1,33,aligned / aligned,,,,,,,0.0," You know, if you look at the way that people's lives have been, you know, lack of jobs, houses, schools, hospitals."
+window,2,,matched,0.495,0.885,0.000626,1.2e-05,1501,1501,,
+segment,2,34,aligned / aligned,,,,,,,0.0," houses, schools, hospitals, stagnated wages, living standards going down or"
+segment,2,35,aligned / aligned,,,,,,,0.0, stagnating for years and years and they feel that mainstream political parties
+segment,2,36,aligned / aligned,,,,,,,0.0, have not met their material needs. What the far right are really good at is
+segment,2,37,aligned / aligned,,,,,,,0.0, going to those people and they turn up and they say you're right to be angry and
+segment,2,38,aligned / aligned,,,,,,,0.0, they give them a scapegoat and they say it's because someone has come to this
+segment,2,39,aligned / aligned,,,,,,,0.0, country and taken it from. They're really good at redirecting people's
+segment,2,40,aligned / aligned,,,,,,,0.0, anger from where it should be directed. I've seen exactly what Joe's talking
+segment,2,41,aligned / aligned,,,,,,,0.0, about. There have been hundreds of protests across the country over the
+segment,2,42,aligned / aligned,,,,,,,0.0, past year according to activists tracking far-right movements. It's mostly been
+segment,2,43,aligned / aligned,,,,,,,0.0, about migration and how consecutive governments have dealt with this issue.
+segment,2,44,aligned / aligned,,,,,,,0.0," And with the center left, labor party back in power for the first time in two"
+segment,2,45,aligned / aligned,,,,,,,0.0," decades, the far-right senses conditions are ripe for resurgence. It's in tight-knit"
+segment,2,46,aligned / aligned,,,,,,,0.0, communities like this one in the sleepy market town of Faversham outside London
+segment,2,47,aligned / aligned,,,,,,,0.0, where we saw it all play out late last year. Walking through town
+window,3,,matched,0.47,0.866,0.040859,2.6e-05,1501,1501,,
+segment,3,48,aligned / aligned,,,,,,,0.0," here. Walking through town with a protest organized by a far right activist, you see those divisions"
+segment,3,49,aligned / aligned,,,,,,,0.0, and feel the anger.
+segment,3,50,aligned / aligned,,,,,,,0.0," ""Shame on me!"""
+segment,3,51,aligned / aligned,,,,,,,0.0," ""Shame on me!"""
+segment,3,52,aligned / aligned,,,,,,,0.0," ""Shame on me!"""
+segment,3,53,aligned / aligned,,,,,,,0.0," ""Right now, they're marching towards this facility where unaccompanied minors asylum seekers"
+segment,3,54,aligned / aligned,,,,,,,0.0," have been housed in this town."""
+segment,3,55,aligned / aligned,,,,,,,0.0," ""I'm straight!"""
+segment,3,56,aligned / aligned,,,,,,,0.0," ""I'm straight!"""
+segment,3,57,aligned / aligned,,,,,,,0.0," They're a loud crowd, but it's clear they're more noise than numbers."
+segment,3,58,aligned / aligned,,,,,,,0.0, And you do see locals coming out to confront them.
+segment,3,59,aligned / aligned,,,,,,,0.0," ""Hey!"
+segment,3,60,aligned / aligned,,,,,,,0.0, Right there!
+segment,3,61,aligned / aligned,,,,,,,0.0," Right, you two, so welcome here!"""
+segment,3,62,aligned / aligned,,,,,,,0.0," The main event kicks off with a rambling mix of racist rhetoric, fear-mongering, and white"
+segment,3,63,aligned / aligned,,,,,,,0.0, supremacist conspiracy theories.
+segment,3,64,aligned / aligned,,,,,,,0.0," ""They're teaching about Muhammad and Allah."
+segment,3,65,aligned / aligned,,,,,,,0.0," We view more terror to children to be too about ABGTQ and what partners are belief, what they"
+segment,3,66,aligned / aligned,,,,,,,0.0, can identify as.
+segment,3,67,aligned / aligned,,,,,,,0.0," We view more terror to that one."""
+segment,3,68,aligned / aligned,,,,,,,0.0," What they can identify as, we've been there to hate that round here."
+window,4,,matched,0.45,0.832,0.000528,9e-06,1501,1501,,
+segment,4,69,aligned / aligned,,,,,,,0.0, Keep up the pressure and one day you will be victorious!
+segment,4,70,aligned / aligned,,,,,,,0.0," At this one tiny town's protest, we find one of the leaders of the UK's extreme right."
+segment,4,71,aligned / aligned,,,,,,,0.0, I can't just be taken over by my immigration.
+segment,4,72,aligned / aligned,,,,,,,0.0," We're fed up. This is not the future that our granddad, grandparents and great-grandparents"
+segment,4,73,aligned / aligned,,,,,,,0.0, fought for in two world wars. Many fight for this to be done to our country.
+segment,4,74,aligned / aligned,,,,,,,0.0, I live in these land and white groups.
+segment,4,75,aligned / aligned,,,,,,,0.0, We want our country to be like it was before this immigration invasion was voiced in on us.
+segment,4,76,aligned / aligned,,,,,,,0.0," Yes, you mentioned far right neo-narcia all that a minute ago."
+segment,4,77,aligned / aligned,,,,,,,0.0, As if that kind of stuff doesn't hold any power anymore.
+segment,4,78,aligned / aligned,,,,,,,0.0, You must have known this with Trump's victory.
+segment,4,79,aligned / aligned,,,,,,,0.0, No one cares if they call it racist.
+segment,4,80,aligned / aligned,,,,,,,0.0, Those terms are just used to silence people.
+segment,4,81,aligned / aligned,,,,,,,0.0, The reelection of Donald Trump does not only mean inspiration for this one extreme right figure.
+segment,4,82,aligned / aligned,,,,,,,0.0," At every far right event I've been to, it is a constant theme."
+segment,4,83,aligned / aligned,,,,,,,0.0, Trump's Make America Great Again has come to the UK.
+segment,4,84,aligned / aligned,,,,,,,0.0, has come to the UK.
+window,5,,matched,0.446,0.835,0.000225,1.2e-05,1501,1501,,
+segment,5,85,aligned / aligned,,,,,,,0.0," This is mega, make England great again."
+segment,5,86,aligned / aligned,,,,,,,0.0, I have so much respect for President Trump.
+segment,5,87,aligned / aligned,,,,,,,0.0," He is saving, not just America,"
+segment,5,88,aligned / aligned,,,,,,,0.0, he is saving the West and in saving the world.
+segment,5,89,aligned / aligned,,,,,,,0.0, You are wearing this because...
+segment,5,90,aligned / aligned,,,,,,,0.0, Because I'm a Donald fan.
+segment,5,91,aligned / aligned,,,,,,,0.0, What is it that's going on?
+segment,5,92,aligned / aligned,,,,,,,0.0, How much of this is really influence from the US?
+segment,5,93,aligned / aligned,,,,,,,0.0, There's no question there's a huge influence.
+segment,5,94,aligned / aligned,,,,,,,0.0," When the far right is small little fringe political parties,"
+segment,5,95,aligned / aligned,,,,,,,0.0, that sounds fanciful.
+segment,5,96,aligned / aligned,,,,,,,0.0," When you've got Donald Trump in the White House,"
+segment,5,97,aligned / aligned,,,,,,,0.0," the most powerful man in the world,"
+segment,5,98,aligned / aligned,,,,,,,0.0," they can then point someone and say,"
+segment,5,99,aligned / aligned,,,,,,,0.0," ""Look, it's happened there. If it can happen there, it can happen here."""
+segment,5,100,aligned / aligned,,,,,,,0.0, Are we headed into a direction where the far right is turning
+segment,5,101,aligned / aligned,,,,,,,0.0, into a significant political force in Britain?
+segment,5,102,aligned / aligned,,,,,,,0.0," I think there's no doubt about it, right?"
+segment,5,103,aligned / aligned,,,,,,,0.0, The far right is no longer something that sits on the very margins
+segment,5,104,aligned / aligned,,,,,,,0.0, of our politics in Britain and annoyance to the right.
+segment,5,105,aligned / aligned,,,,,,,0.0, It is increasingly something that actually has the real chance of taking the right.
+segment,5,106,aligned / aligned,,,,,,,0.0, it is increasingly something that actually has the real chance of taking power in Britain.
+window,6,,matched,0.127,0.147,0.000168,1.1e-05,396,396,,
+segment,6,107,aligned / aligned,,,,,,,0.0, The once fringe voices seem to be moving into the mainstream.
+segment,6,108,aligned / aligned,,,,,,,0.0, It's a small but vocal minority that's threatening to change the face of Britain.
+segment,6,109,aligned / aligned,,,,,,,0.0, Now they believe their moment has arrived.

stt_en_conformer_ctc_small_features.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8998fd44bc2374c7d085f7c709fbfbd28ea6db09998622077071faf478db24fd
+size 53197388

tokenizer/model_config.yaml

@@ -0,0 +1,1136 @@
+sample_rate: 16000
+log_prediction: true
+ctc_reduction: mean_batch
+train_ds:
+  manifest_filepath: /data/NeMo_ASR_SET/English/v2.0/train/tarred_audio_manifest.json
+  sample_rate: 16000
+  batch_size: 64
+  shuffle: true
+  num_workers: 8
+  pin_memory: true
+  use_start_end_token: false
+  trim_silence: false
+  max_duration: 20.0
+  min_duration: 0.1
+  shuffle_n: 2048
+  is_tarred: true
+  tarred_audio_filepaths: /data/NeMo_ASR_SET/English/v2.0/train/audio__OP_0..4095_CL_.tar
+validation_ds:
+  manifest_filepath:
+  - /data/ASR/LibriSpeech/librispeech_withsp2/manifests/librivox-dev-other.json
+  - /data/ASR/LibriSpeech/librispeech_withsp2/manifests/librivox-dev-clean.json
+  - /data/ASR/LibriSpeech/librispeech_withsp2/manifests/librivox-test-other.json
+  - /data/ASR/LibriSpeech/librispeech_withsp2/manifests/librivox-test-clean.json
+  sample_rate: 16000
+  batch_size: 64
+  shuffle: false
+  num_workers: 8
+  pin_memory: true
+  use_start_end_token: false
+  is_tarred: false
+  tarred_audio_filepaths: na
+test_ds:
+  manifest_filepath:
+  - /data/ASR/LibriSpeech/librispeech_withsp2/manifests/librivox-test-other.json
+  - /data/ASR/LibriSpeech/librispeech_withsp2/manifests/librivox-dev-clean.json
+  - /data/ASR/LibriSpeech/librispeech_withsp2/manifests/librivox-dev-other.json
+  - /data/ASR/LibriSpeech/librispeech_withsp2/manifests/librivox-test-clean.json
+  sample_rate: 16000
+  batch_size: 64
+  shuffle: false
+  num_workers: 8
+  pin_memory: true
+  use_start_end_token: false
+  is_tarred: false
+  tarred_audio_filepaths: na
+tokenizer:
+  dir: /tokenizers/NeMo_ASR_SET/English/asr_set_2.0/tokenizer_spe_unigram_v1024/
+  type: bpe
+  model_path: nemo:977d4e24975b431ebb44f2dfcdea8778_tokenizer.model
+  vocab_path: nemo:29fcf21b9e6e4fb5b1ba0bb1efd4197e_vocab.txt
+  spe_tokenizer_vocab: nemo:cf241f7e4d904eaea46bb96f21dd0b1d_tokenizer.vocab
+preprocessor:
+  _target_: nemo.collections.asr.modules.AudioToMelSpectrogramPreprocessor
+  sample_rate: 16000
+  normalize: per_feature
+  window_size: 0.025
+  window_stride: 0.01
+  window: hann
+  features: 80
+  n_fft: 512
+  log: true
+  frame_splicing: 1
+  dither: 1.0e-05
+  pad_to: 0
+  pad_value: 0.0
+spec_augment:
+  _target_: nemo.collections.asr.modules.SpectrogramAugmentation
+  freq_masks: 2
+  time_masks: 5
+  freq_width: 27
+  time_width: 0.05
+encoder:
+  _target_: nemo.collections.asr.modules.ConformerEncoder
+  feat_in: 80
+  feat_out: -1
+  n_layers: 16
+  d_model: 176
+  subsampling: striding
+  subsampling_factor: 4
+  subsampling_conv_channels: 176
+  ff_expansion_factor: 4
+  self_attention_model: rel_pos
+  n_heads: 4
+  att_context_size:
+  - -1
+  - -1
+  xscaling: true
+  untie_biases: true
+  pos_emb_max_len: 5000
+  conv_kernel_size: 31
+  dropout: 0.1
+  dropout_emb: 0.0
+  dropout_att: 0.1
+decoder:
+  _target_: nemo.collections.asr.modules.ConvASRDecoder
+  feat_in: 176
+  num_classes: 1024
+  vocabulary:
+  - <unk>
+  - s
+  - ▁the
+  - ▁a
+  - t
+  - ▁to
+  - ▁and
+  - ▁i
+  - ▁of
+  - ''''
+  - ed
+  - ▁in
+  - d
+  - ing
+  - 'n'
+  - e
+  - ▁it
+  - ▁that
+  - ▁you
+  - 'y'
+  - er
+  - r
+  - ▁for
+  - m
+  - ▁is
+  - ▁he
+  - re
+  - ▁was
+  - ▁be
+  - p
+  - ly
+  - ▁so
+  - ▁we
+  - a
+  - g
+  - o
+  - ▁c
+  - b
+  - u
+  - ▁on
+  - ▁have
+  - ▁but
+  - ll
+  - ▁with
+  - ▁re
+  - or
+  - ▁s
+  - al
+  - ▁do
+  - ▁know
+  - ar
+  - ▁they
+  - ▁not
+  - ▁as
+  - ▁this
+  - in
+  - le
+  - ▁e
+  - ▁are
+  - ▁like
+  - c
+  - ▁uh
+  - ri
+  - ▁me
+  - ▁his
+  - ▁at
+  - l
+  - es
+  - ▁de
+  - ▁yeah
+  - ▁can
+  - k
+  - ▁or
+  - ▁my
+  - ▁all
+  - ▁had
+  - ▁there
+  - ▁will
+  - ▁one
+  - il
+  - ▁no
+  - ▁what
+  - en
+  - ck
+  - ▁b
+  - ▁f
+  - ce
+  - ch
+  - i
+  - ▁by
+  - ▁she
+  - ▁from
+  - ▁an
+  - ic
+  - ur
+  - ve
+  - w
+  - ter
+  - la
+  - ▁if
+  - ▁just
+  - th
+  - li
+  - ▁
+  - ▁her
+  - ▁um
+  - 'on'
+  - ation
+  - ▁w
+  - ▁would
+  - f
+  - te
+  - ▁st
+  - ▁go
+  - ir
+  - it
+  - ▁out
+  - ro
+  - ▁pa
+  - ▁were
+  - ▁g
+  - ▁t
+  - ion
+  - ▁think
+  - an
+  - ▁right
+  - ▁about
+  - se
+  - lo
+  - ent
+  - ▁up
+  - ment
+  - ate
+  - ▁when
+  - h
+  - ne
+  - ▁don
+  - ▁has
+  - ▁also
+  - ▁more
+  - ▁see
+  - ▁okay
+  - ▁their
+  - ▁your
+  - ge
+  - ▁who
+  - ▁well
+  - ▁co
+  - ▁which
+  - ▁some
+  - ▁se
+  - ▁time
+  - ▁ba
+  - ▁said
+  - ▁con
+  - ers
+  - ▁ra
+  - us
+  - de
+  - ra
+  - ▁him
+  - ▁our
+  - ▁been
+  - ▁fa
+  - ▁po
+  - ▁pro
+  - et
+  - x
+  - ▁la
+  - id
+  - ver
+  - ▁oh
+  - ▁ma
+  - v
+  - ▁now
+  - age
+  - ▁two
+  - ld
+  - ▁mo
+  - ▁how
+  - tion
+  - ▁people
+  - ive
+  - ▁other
+  - ng
+  - ity
+  - z
+  - ist
+  - ▁very
+  - ▁get
+  - ▁any
+  - ▁un
+  - ▁ro
+  - is
+  - ▁work
+  - ▁mean
+  - ▁them
+  - ▁lo
+  - vi
+  - ▁because
+  - ies
+  - ul
+  - as
+  - ad
+  - mp
+  - ▁bo
+  - '-'
+  - ▁then
+  - ▁good
+  - el
+  - nd
+  - ▁li
+  - ▁man
+  - ▁dis
+  - ▁could
+  - ▁ho
+  - at
+  - ol
+  - ▁bu
+  - ▁te
+  - ▁ha
+  - est
+  - me
+  - ▁say
+  - ru
+  - ke
+  - ▁sp
+  - ▁k
+  - able
+  - ▁su
+  - ▁sa
+  - ▁di
+  - ▁fi
+  - ance
+  - ▁really
+  - ▁over
+  - ▁even
+  - ry
+  - ▁us
+  - ▁ca
+  - ow
+  - ho
+  - ▁into
+  - ence
+  - mo
+  - ▁mi
+  - one
+  - qu
+  - ut
+  - lu
+  - ▁o
+  - ty
+  - ▁after
+  - ▁want
+  - ▁new
+  - ▁take
+  - ▁p
+  - ▁look
+  - ▁pre
+  - sh
+  - ▁day
+  - ▁should
+  - ▁th
+  - ▁need
+  - ▁cha
+  - co
+  - ▁much
+  - ▁where
+  - ▁d
+  - ant
+  - ▁fe
+  - ▁da
+  - ▁make
+  - om
+  - ▁did
+  - ▁le
+  - un
+  - ▁only
+  - im
+  - ▁these
+  - ff
+  - ti
+  - ish
+  - ▁ex
+  - ted
+  - ▁first
+  - he
+  - ig
+  - ▁vi
+  - ▁ri
+  - ▁en
+  - ▁com
+  - ated
+  - ▁than
+  - ma
+  - ▁way
+  - um
+  - ct
+  - end
+  - ight
+  - ▁here
+  - ▁ta
+  - ▁car
+  - ▁part
+  - ▁come
+  - ia
+  - ▁off
+  - ▁sc
+  - ▁ah
+  - am
+  - ▁tra
+  - ▁yes
+  - ▁back
+  - ture
+  - ful
+  - ▁pri
+  - ction
+  - ine
+  - ▁three
+  - ard
+  - ▁let
+  - pe
+  - ▁little
+  - ▁down
+  - mb
+  - ▁si
+  - ▁dr
+  - ▁mr
+  - ▁going
+  - ▁comp
+  - po
+  - ▁m
+  - ▁sta
+  - ▁gra
+  - day
+  - ▁many
+  - ian
+  - ta
+  - ▁long
+  - ▁pi
+  - ▁too
+  - ▁app
+  - ▁kind
+  - ous
+  - ci
+  - ▁ga
+  - ten
+  - nt
+  - ▁before
+  - ▁may
+  - ▁got
+  - man
+  - tic
+  - ition
+  - cu
+  - ugh
+  - tra
+  - ▁n
+  - ward
+  - ▁give
+  - ▁every
+  - ▁hi
+  - ting
+  - ▁exp
+  - ▁those
+  - ▁hu
+  - ot
+  - ▁something
+  - ▁lot
+  - ▁still
+  - ▁ne
+  - na
+  - ise
+  - pp
+  - ▁most
+  - ▁gu
+  - ▁state
+  - ▁actually
+  - ▁such
+  - ▁bi
+  - ▁never
+  - tain
+  - ▁great
+  - ▁through
+  - ▁al
+  - 'no'
+  - ▁mar
+  - ▁year
+  - ach
+  - les
+  - ▁school
+  - ally
+  - ial
+  - ha
+  - ▁old
+  - ▁made
+  - ary
+  - ▁ar
+  - ▁years
+  - ▁help
+  - ▁per
+  - ving
+  - ical
+  - ther
+  - ▁does
+  - ac
+  - ca
+  - ▁must
+  - di
+  - ▁own
+  - ▁ru
+  - ▁things
+  - ▁hand
+  - ▁thing
+  - ▁high
+  - ▁last
+  - go
+  - ▁sh
+  - ▁under
+  - ▁four
+  - ▁place
+  - ations
+  - ▁sure
+  - mi
+  - nce
+  - ▁am
+  - for
+  - ness
+  - ▁name
+  - ▁five
+  - ound
+  - ▁op
+  - ▁cons
+  - ▁ph
+  - ▁same
+  - row
+  - ven
+  - ph
+  - ite
+  - ▁pe
+  - j
+  - ▁sha
+  - ▁friend
+  - ▁wi
+  - ▁call
+  - ▁european
+  - ▁h
+  - ect
+  - ress
+  - ▁live
+  - port
+  - ▁mhm
+  - ▁house
+  - ie
+  - ni
+  - ▁plan
+  - ▁jo
+  - ▁play
+  - side
+  - ▁va
+  - min
+  - ious
+  - ▁life
+  - ▁du
+  - ▁ti
+  - ▁six
+  - ▁men
+  - ▁again
+  - ▁thank
+  - ▁talk
+  - par
+  - ▁home
+  - op
+  - ▁both
+  - ▁why
+  - ▁put
+  - ▁another
+  - nc
+  - ▁being
+  - mit
+  - ▁came
+  - led
+  - ▁fo
+  - ▁end
+  - ▁member
+  - ative
+  - ▁thought
+  - ▁tri
+  - iv
+  - our
+  - red
+  - ▁went
+  - lic
+  - ▁find
+  - ▁pu
+  - land
+  - ▁start
+  - ▁far
+  - ▁eu
+  - ▁imp
+  - ▁always
+  - ▁ju
+  - ▁wa
+  - ▁person
+  - ▁singapore
+  - ap
+  - ▁show
+  - ▁chi
+  - ▁ten
+  - ▁eight
+  - ▁while
+  - ▁point
+  - ▁y
+  - ▁ja
+  - ▁ya
+  - ling
+  - ctor
+  - ▁use
+  - ▁acc
+  - ▁world
+  - ▁pay
+  - ▁read
+  - va
+  - vo
+  - ▁change
+  - ▁u
+  - ▁pl
+  - ▁sw
+  - ▁war
+  - ▁might
+  - nk
+  - ments
+  - and
+  - ▁different
+  - ▁dec
+  - cent
+  - ▁ste
+  - ▁better
+  - ▁fun
+  - ▁month
+  - ship
+  - ton
+  - ▁tell
+  - ▁twenty
+  - ▁commission
+  - ▁exc
+  - ▁miss
+  - if
+  - ▁love
+  - ▁money
+  - ▁found
+  - ▁hundred
+  - gg
+  - ▁add
+  - ▁real
+  - ities
+  - ▁na
+  - ▁pass
+  - ▁didn
+  - ▁v
+  - ▁feel
+  - ▁week
+  - ▁win
+  - ible
+  - ▁try
+  - ▁upon
+  - ba
+  - ▁interest
+  - ▁inter
+  - son
+  - line
+  - ▁ob
+  - ▁boy
+  - ▁big
+  - ▁used
+  - ▁seven
+  - ▁away
+  - ▁family
+  - less
+  - ▁ki
+  - ber
+  - ▁around
+  - ▁turn
+  - ▁anything
+  - ▁care
+  - ▁young
+  - ▁guess
+  - ▁happen
+  - ▁course
+  - ▁agree
+  - ▁support
+  - ▁conf
+  - ual
+  - ▁number
+  - ▁trans
+  - ating
+  - ▁mister
+  - ▁hard
+  - ▁watch
+  - ft
+  - ▁next
+  - ▁sea
+  - ▁open
+  - ▁without
+  - duc
+  - gra
+  - ak
+  - ▁cap
+  - ▁cre
+  - hi
+  - ▁government
+  - ▁vo
+  - ▁between
+  - ▁each
+  - ▁ve
+  - ▁though
+  - ▁country
+  - ▁few
+  - ▁once
+  - ▁'
+  - ▁head
+  - ▁free
+  - ▁mu
+  - ▁maybe
+  - ▁act
+  - ▁night
+  - ▁thousand
+  - ▁face
+  - ▁uhhuh
+  - ▁keep
+  - ▁nine
+  - ▁close
+  - ▁case
+  - ▁che
+  - ▁against
+  - ▁done
+  - ▁ever
+  - ▁law
+  - ▁believe
+  - ▁public
+  - ▁room
+  - ▁sub
+  - ▁order
+  - ▁important
+  - ient
+  - ▁el
+  - ▁children
+  - ▁second
+  - ▁bri
+  - ▁business
+  - ▁hope
+  - ▁move
+  - fa
+  - ▁however
+  - ▁follow
+  - ▁able
+  - ▁word
+  - ▁yet
+  - ▁fla
+  - ▁stand
+  - ize
+  - ▁je
+  - ▁service
+  - ▁nothing
+  - ▁report
+  - ▁called
+  - ▁grow
+  - ▁continue
+  - ▁issue
+  - ▁since
+  - ▁book
+  - ▁lu
+  - ▁qui
+  - ▁develop
+  - ▁gen
+  - ▁certain
+  - light
+  - ▁cor
+  - ▁small
+  - ▁took
+  - ▁question
+  - ▁whole
+  - ▁problem
+  - ▁side
+  - ▁child
+  - ▁full
+  - ▁best
+  - ▁mm
+  - ▁probably
+  - fi
+  - ▁qua
+  - ▁sur
+  - ▁market
+  - ▁left
+  - ▁everything
+  - ▁during
+  - ▁understand
+  - ook
+  - wa
+  - ▁cent
+  - ▁water
+  - ▁quite
+  - ▁leave
+  - ▁himself
+  - ip
+  - ▁near
+  - ▁saw
+  - ▁together
+  - ▁large
+  - ▁having
+  - ▁already
+  - ▁invest
+  - ▁pretty
+  - ▁direct
+  - ▁hour
+  - ▁fact
+  - way
+  - ▁run
+  - ▁bra
+  - ▁clear
+  - ▁fra
+  - ▁area
+  - ▁union
+  - ▁enough
+  - ▁consider
+  - ▁lead
+  - ▁remain
+  - ▁president
+  - ▁system
+  - ▁def
+  - ▁stuff
+  - ▁food
+  - ▁job
+  - ▁heard
+  - ▁err
+  - ▁mind
+  - ▁rest
+  - ▁speak
+  - ▁asked
+  - ator
+  - ▁half
+  - ▁father
+  - com
+  - ▁less
+  - ▁arm
+  - ▁human
+  - ency
+  - ▁matter
+  - ▁group
+  - ▁girl
+  - ▁current
+  - ▁main
+  - ttle
+  - ▁later
+  - ▁learn
+  - ▁strong
+  - ▁sign
+  - ▁check
+  - ▁light
+  - ▁else
+  - ▁true
+  - ▁term
+  - qui
+  - ▁minute
+  - ▁spec
+  - ▁return
+  - ▁answer
+  - ▁reason
+  - ▁count
+  - ▁shall
+  - ▁communi
+  - ▁travel
+  - ▁wait
+  - ▁provide
+  - ▁low
+  - ▁mother
+  - ▁expect
+  - ▁cause
+  - ▁line
+  - ▁general
+  - lf
+  - ▁getting
+  - ▁parliament
+  - ▁bank
+  - ▁company
+  - ▁stop
+  - cause
+  - ▁power
+  - ▁gi
+  - ▁europe
+  - ▁moment
+  - ▁among
+  - ▁walk
+  - ▁allow
+  - ▁idea
+  - ▁office
+  - ▁town
+  - ▁cannot
+  - ▁countries
+  - ▁become
+  - ▁appear
+  - ▁present
+  - ▁bring
+  - ▁least
+  - ▁almost
+  - ▁kids
+  - ▁remember
+  - ▁include
+  - ▁short
+  - ▁sometimes
+  - ▁game
+  - ▁level
+  - ▁exactly
+  - ▁particular
+  - ▁social
+  - ▁land
+  - ▁woman
+  - ▁north
+  - ▁nice
+  - ▁concern
+  - ▁sort
+  - ▁effect
+  - ▁national
+  - ▁several
+  - ▁safe
+  - ▁until
+  - ▁further
+  - ▁cost
+  - ▁wonder
+  - ▁whether
+  - ▁either
+  - ▁future
+  - ▁pra
+  - ▁council
+  - ▁knew
+  - ▁common
+  - ▁south
+  - ▁making
+  - ▁morning
+  - ▁process
+  - ▁situation
+  - ▁white
+  - ▁result
+  - ▁suppose
+  - ▁employ
+  - ▁political
+  - ▁program
+  - ▁along
+  - ▁women
+  - ▁ski
+  - ▁court
+  - ▁please
+  - ▁shi
+  - ▁possible
+  - ▁protect
+  - ▁experience
+  - ▁definitely
+  - ▁require
+  - ▁account
+  - ▁myself
+  - ▁black
+  - ▁example
+  - ▁america
+  - ▁thirty
+  - ▁student
+  - ▁view
+  - ▁product
+  - ▁wife
+  - ▁health
+  - ▁major
+  - ▁difficult
+  - ▁death
+  - ▁visit
+  - ▁across
+  - ▁receive
+  - ▁voice
+  - ▁citizen
+  - ▁regard
+  - ▁author
+  - ▁treat
+  - ▁especially
+  - ▁local
+  - ▁taking
+  - ▁information
+  - ▁seemed
+  - ▁success
+  - ability
+  - ▁break
+  - ▁whatever
+  - ▁security
+  - ▁address
+  - ▁felt
+  - ▁fifty
+  - ▁million
+  - ▁third
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+    warmup_steps: 10000
+    warmup_ratio: null
+    min_lr: 1.0e-06
+target: nemo.collections.asr.models.ctc_bpe_models.EncDecCTCModelBPE

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tokenizer/vocab.txt

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