Parseh aligner hi v1: ONNX int8 from ai4bharat/indicwav2vec-hindi@e746fa3e8de3f6629b9ded29d9c1c565c566f3db

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NOTICE

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+Parseh ONNX aligner — Hindi
+
+Derived from ai4bharat/indicwav2vec-hindi at immutable revision e746fa3e8de3f6629b9ded29d9c1c565c566f3db.
+Base model: AI4Bharat IndicWav2Vec (exact upstream base revision not stated in public Hub metadata).
+
+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:
+- None declared
+
+The original source model licence is apache-2.0. This derivative carries the applicable licence text and required attribution; no endorsement is implied.
+
+AI4Bharat’s IndicWav2Vec repository separately states that MIT applies to its pretrained, fine-tuned and language models; this is retained as upstream provenance alongside this checkpoint’s Apache-2.0 Hub tag.

README.md

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+---
+license: apache-2.0
+language: hi
+library_name: onnx
+tags:
+- onnx
+- wav2vec2
+- ctc
+- forced-alignment
+- quantized
+- parseh
+base_model: ai4bharat/indicwav2vec-hindi
+base_model_relation: quantized
+---
+
+# Parseh Hindi forced-alignment network
+
+This CTC network aligns known Hindi 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 [ai4bharat/indicwav2vec-hindi](https://huggingface.co/ai4bharat/indicwav2vec-hindi) at `e746fa3e8de3f6629b9ded29d9c1c565c566f3db`, based on `AI4Bharat IndicWav2Vec (exact upstream base revision not stated in public Hub metadata)`. 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: `6.67572021484375e-05`; frame-argmax agreement: `1.0`.
+- 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: `4.991424` s; peak RSS: `2877698048` 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
+
+No separate citation block was provided by the source card.
+
+## Contact
+
+Contact: [development@parseh.io](mailto:development@parseh.io).

SHA256SUMS

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+d0161482752162ab9f8d4bae7522703fa4a8aa83f7d54b265d84c7f3bff7f568  NOTICE
+af923fe72831b08f23a5f762794f596cb4314518a19b6e65d1ed5af2448dbe16  README.md
+3cca0ad53c37fa74568151da7514c8af0f5f626fef6ef6d7123d523c0387ed7e  meta.json
+2499aa855f4a6d76ba583909f53e677fce3cb54f82104291d2afe80b41eea169  model.int8.onnx
+8f9f560daa144e525174a9ce159ac4d168e010006d6c3e46cad02cae72a6c5ad  preprocessor_config.json
+0c61b05b008701ae1662361276bb65e93433a052b523113a8811b3da6e88b767  vocab.json

meta.json

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+{
+  "format": 1,
+  "language": "hi",
+  "source": {
+    "repo": "ai4bharat/indicwav2vec-hindi",
+    "revision": "e746fa3e8de3f6629b9ded29d9c1c565c566f3db",
+    "license": "apache-2.0",
+    "base_model": "AI4Bharat IndicWav2Vec (exact upstream base revision not stated in public Hub metadata)",
+    "datasets": [],
+    "files": {
+      "README.md": {
+        "sha256": "0f44b9db7abbfc4904aac472d01b23307295ef05d548dae4ee663bac145d0d6b",
+        "size": 1576
+      },
+      "config.json": {
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+        "size": 2100
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+      "pytorch_model.bin": {
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+        "size": 1262181719
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+      "special_tokens_map.json": {
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+        "size": 85
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+      "tokenizer_config.json": {
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+        "size": 257
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+      "vocab.json": {
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+        "size": 741
+      }
+    }
+  },
+  "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": 68,
+    "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": 6.67572021484375e-05,
+    "frame_argmax_agreement_fp32_vs_torch": 1.0,
+    "frame_argmax_agreement_int8": 1.0,
+    "fp32_size": 1262467939,
+    "int8_size": 356334100,
+    "frames": 49,
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+            "seconds": 8.864183
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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": 4.991424,
+      "peak_rss_bytes": 2877698048
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+    "synthetic_sentence": {
+      "voice": "hi",
+      "caption": "\u0928\u092e\u0938\u094d\u0924\u0947 \u0926\u0941\u0928\u093f\u092f\u093e",
+      "samples": 17870,
+      "note": "pipeline/monotonicity check only; not an accuracy claim"
+    }
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+  "files": {
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+}

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,
+  "processor_class": "Wav2Vec2ProcessorWithLM",
+  "return_attention_mask": true,
+  "sampling_rate": 16000
+}

vocab.json

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+{"<s>": 1, "<pad>": 0, "</s>": 2, "<unk>": 3, "|": 4, "ँ": 5, "ं": 6, "ः": 7, "अ": 8, "आ": 9, "इ": 10, "ई": 11, "उ": 12, "ऊ": 13, "ऋ": 14, "ए": 15, "ऐ": 16, "ऑ": 17, "ओ": 18, "औ": 19, "क": 20, "ख": 21, "ग": 22, "घ": 23, "ङ": 24, "च": 25, "छ": 26, "ज": 27, "झ": 28, "ञ": 29, "ट": 30, "ठ": 31, "ड": 32, "ढ": 33, "ण": 34, "त": 35, "थ": 36, "द": 37, "ध": 38, "न": 39, "प": 40, "फ": 41, "ब": 42, "भ": 43, "म": 44, "य": 45, "र": 46, "ल": 47, "व": 48, "श": 49, "ष": 50, "स": 51, "ह": 52, "़": 53, "ा": 54, "ि": 55, "ी": 56, "ु": 57, "ू": 58, "ृ": 59, "ॅ": 60, "े": 61, "ै": 62, "ॉ": 63, "ो": 64, "ौ": 65, "्": 66, "ळ": 67}