Parseh aligner fr v1: ONNX int8 from jonatasgrosman/wav2vec2-large-xlsr-53-french@7c79e105a6525d38e1e69f640b974b4a679723cc

LICENSE

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NOTICE

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+Parseh ONNX aligner — French
+
+Derived from jonatasgrosman/wav2vec2-large-xlsr-53-french at immutable revision 7c79e105a6525d38e1e69f640b974b4a679723cc.
+Base model: facebook/wav2vec2-large-xlsr-53.
+
+Changes made: converted the CTC checkpoint to ONNX (opset 17) and dynamically quantized MatMul weights to int8. No retraining was performed.
+
+Training material named by the source card:
+- Mozilla Common Voice (CC0)
+
+The original source model licence is apache-2.0. This derivative carries the applicable licence text and required attribution; no endorsement is implied.

README.md

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+---
+license: apache-2.0
+language: fr
+library_name: onnx
+tags:
+- onnx
+- wav2vec2
+- ctc
+- forced-alignment
+- quantized
+- parseh
+base_model: jonatasgrosman/wav2vec2-large-xlsr-53-french
+base_model_relation: quantized
+datasets:
+- common_voice
+---
+
+# Parseh French forced-alignment network
+
+This CTC network aligns known French caption text to 16 kHz mono audio in Parseh. It is not a general-purpose speech-recognition model. Parseh runs it locally with NumPy and ONNX Runtime, then uses CTC Viterbi alignment for word spans or character spans.
+
+## Provenance and conversion
+
+Derived from [jonatasgrosman/wav2vec2-large-xlsr-53-french](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-french) at `7c79e105a6525d38e1e69f640b974b4a679723cc`, based on `facebook/wav2vec2-large-xlsr-53`. It was converted to ONNX opset 17 and dynamically quantized to int8 (`QUInt8`, per-channel `MatMul` weights); no retraining was performed. Exact source and output hashes are in `meta.json` and `SHA256SUMS`.
+
+## Verification
+
+- ONNX Runtime CPU versions: 1.23.2, 1.30.0; dynamic 0.5 s and 60 s inputs passed.
+- fp32 ONNX/PyTorch log-softmax max absolute difference: `2.86102294921875e-05`; frame-argmax agreement: `None`.
+- int8/fp32 frame-argmax agreement: `1.0`; generated-speech span-start delta median/p95/max: `0.0` / `0.0` / `0.0` ms.
+- Generated 30-second CPU alignment cost: `3.854004` s; peak RSS: `2853023744` bytes.
+
+`espeak-ng` generated audio was used only for pipeline monotonicity, not a real-speech accuracy claim. Unknown characters use a wildcard score to preserve a monotonic path.
+
+## Limitations
+
+Input must be 16 kHz mono audio and known caption text. Noise, accents, text errors, vocabulary gaps, and quantization can affect timestamps. No accuracy guarantee is made. 
+
+## Licence and attribution
+
+The source tag is `apache-2.0`. `LICENSE` and `NOTICE` retain source, base-model, dataset attribution, and changes. No endorsement by original authors, Meta, Mozilla, or Parseh is implied.
+
+## Citation from the source card
+
+```bibtex
+@misc{grosman2021xlsr53-large-french,
+  title={Fine-tuned {XLSR}-53 large model for speech recognition in {F}rench},
+  author={Grosman, Jonatas},
+  howpublished={\url{https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-french}},
+  year={2021}
+}
+```
+
+## Contact
+
+Contact: [development@parseh.io](mailto:development@parseh.io).

SHA256SUMS

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+cfc7749b96f63bd31c3c42b5c471bf756814053e847c10f3eb003417bc523d30  LICENSE
+3eeddfbfb63cf3c0ef1b511ae9f1bb15bd35c35d106b2098299d3e63e2459fea  NOTICE
+c907130933fb454ba8356c168a4e908a82c316f67e91fef024b3fda0e9ae4ef6  README.md
+bf3e37122369535c84ced3d6d9ea99d0f5baceb690bcd59e81bbbedced02d6f8  meta.json
+efd4d759980e6351c0e6610644b733a1bc36f30840b31de29274274fb888cec7  model.int8.onnx
+ca5999a45e98bb76ea87a461ba28a23ad32a5bb9f733b8e0f6546ff38b6c612d  preprocessor_config.json
+e83a3c849e480757fabd9fe927b870581e926407bcc7e1b6dcc8bda1e78a8d78  vocab.json

meta.json

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+{
+  "format": 1,
+  "language": "fr",
+  "source": {
+    "repo": "jonatasgrosman/wav2vec2-large-xlsr-53-french",
+    "revision": "7c79e105a6525d38e1e69f640b974b4a679723cc",
+    "license": "apache-2.0",
+    "base_model": "facebook/wav2vec2-large-xlsr-53",
+    "datasets": [
+      "common_voice"
+    ],
+    "files": {
+      "pytorch_model.bin": {
+        "sha256": "2fc4760bab7bf7d0d6c06e9b7f829a27a3e66eefee3733f53c88dbedf6607f2e",
+        "size": 1262175703
+      },
+      "README.md": {
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+        "size": 5543
+      },
+      "config.json": {
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+        "size": 1531
+      },
+      "preprocessor_config.json": {
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+        "size": 262
+      },
+      "special_tokens_map.json": {
+        "sha256": "bb7068de1150661a10b55f9e4b12a0e77af8bf91f5e45e1b58afaf1d0e17f675",
+        "size": 85
+      },
+      "vocab.json": {
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+        "size": 560
+      }
+    }
+  },
+  "model": {
+    "file": "model.int8.onnx",
+    "precision": "int8-dynamic",
+    "input": "input_values",
+    "output": "logits",
+    "sample_rate": 16000,
+    "frame_samples": 320,
+    "min_samples": 400,
+    "normalize": "zero-mean-unit-variance",
+    "blank_id": 0,
+    "vocab_size": 59,
+    "word_delimiter": "|",
+    "text_case": "preserve",
+    "unit": "char"
+  },
+  "text": {
+    "spaces_separate_words": true,
+    "unknown_characters": "wildcard"
+  },
+  "verify": {
+    "tools": {
+      "onnxruntime": [
+        "1.30.0",
+        "1.23.2"
+      ]
+    },
+    "logit_maxabs_fp32_vs_torch": 2.86102294921875e-05,
+    "frame_argmax_agreement_int8": 1.0,
+    "fp32_size": 1262431039,
+    "int8_size": 356311445,
+    "frames": 49,
+    "runtime": {
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+            "seconds": 14.596255
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+      "1.23.2": {
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+            "seconds": 8.811797
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+    },
+    "word_start_delta_ms_int8_vs_fp32": {
+      "median": 0.0,
+      "p95": 0.0,
+      "max": 0.0,
+      "spans": 2,
+      "test_audio": "espeak-ng generated sentence"
+    },
+    "sanity": {
+      "monotonic_sentence_spans": 2,
+      "unknown_wildcard_spans": 2
+    },
+    "cost": {
+      "audio_seconds": 30,
+      "alignment_seconds": 3.854004,
+      "peak_rss_bytes": 2853023744
+    },
+    "synthetic_sentence": {
+      "voice": "fr-fr",
+      "caption": "bonjour monde",
+      "samples": 14702,
+      "note": "pipeline/monotonicity check only; not an accuracy claim"
+    }
+  },
+  "files": {
+    "model.int8.onnx": {
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+      "size": 356311445
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+  },
+  "elapsed_seconds": 41.258
+}

model.int8.onnx

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preprocessor_config.json

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+{
+  "do_normalize": true,
+  "feature_extractor_type": "Wav2Vec2FeatureExtractor",
+  "feature_size": 1,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "return_attention_mask": true,
+  "sampling_rate": 16000,
+  "processor_class": "Wav2Vec2ProcessorWithLM"
+}

vocab.json

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