Parseh aligner tr v1: ONNX int8 from mpoyraz/wav2vec2-xls-r-300m-cv7-turkish@708639f50559d7970f462e13ec64d3f059ca89f6

LICENSE

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+Creative Commons may be contacted at creativecommons.org.
+

NOTICE

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+Parseh ONNX aligner — Turkish
+
+Derived from mpoyraz/wav2vec2-xls-r-300m-cv7-turkish at immutable revision 708639f50559d7970f462e13ec64d3f059ca89f6.
+Base model: facebook/wav2vec2-large-xls-r-300m.
+
+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 7.0 (CC0)
+- MediaSpeech (CC-BY-4.0; https://creativecommons.org/licenses/by/4.0/)
+
+The original source model licence is cc-by-4.0. This derivative carries the applicable licence text and required attribution; no endorsement is implied.

README.md

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+---
+license: cc-by-4.0
+language: tr
+library_name: onnx
+tags:
+- onnx
+- wav2vec2
+- ctc
+- forced-alignment
+- quantized
+- parseh
+base_model: mpoyraz/wav2vec2-xls-r-300m-cv7-turkish
+base_model_relation: quantized
+datasets:
+- common_voice_7_0
+- mediaspeech
+---
+
+# Parseh Turkish forced-alignment network
+
+This CTC network aligns known Turkish 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 [mpoyraz/wav2vec2-xls-r-300m-cv7-turkish](https://huggingface.co/mpoyraz/wav2vec2-xls-r-300m-cv7-turkish) at `708639f50559d7970f462e13ec64d3f059ca89f6`, based on `facebook/wav2vec2-large-xls-r-300m`. 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: `9.5367431640625e-06`; 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: `6.663475` s; peak RSS: `2870992896` 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 `cc-by-4.0`. `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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+9ba9550ad48438d0836ddab3da480b3b69ffa0aac7b7878b5a0039e7ab429411  LICENSE
+d193ea8d7e0ddc528988a1d75e2300b0e41faffa9aab0316eb65193b258542a6  NOTICE
+0466845439d6e0312ecdf2bde1b3311b0bd373bee76221500d7e06a4299f4ceb  README.md
+2ae007849038116de688bb77efddfd00d168d4d8452140e595f3ecb1193b135e  meta.json
+6ba1e92e5bdeb2d9b4c23d555728f18313c89fe630bf9c55f9d0e09a62c87c74  model.int8.onnx
+94c00f2bccbdbf4891a1ed8be371e59debaedd03d64f5e8313cedfa4c60da22b  preprocessor_config.json
+6641ad4761f75bbba7ca2591b1eaef57d1ab444762bf6a51f2ddbd70bfe3ee2f  vocab.json

meta.json

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+{
+  "format": 1,
+  "language": "tr",
+  "source": {
+    "repo": "mpoyraz/wav2vec2-xls-r-300m-cv7-turkish",
+    "revision": "708639f50559d7970f462e13ec64d3f059ca89f6",
+    "license": "cc-by-4.0",
+    "base_model": "facebook/wav2vec2-xls-r-300m",
+    "datasets": [
+      "common_voice_7_0",
+      "mediaspeech"
+    ],
+    "files": {
+      "pytorch_model.bin": {
+        "sha256": "008d69c82bf45c82ec5485e550abc86ddabefe75080f22e1ebfdc1699889d82e",
+        "size": 1262079473
+      },
+      "README.md": {
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+        "size": 3554
+      },
+      "config.json": {
+        "sha256": "8c8c02e416aaca6f258fd270eec4d646e8ad60a7a2bc6516f37cef9f21589df5",
+        "size": 2035
+      },
+      "preprocessor_config.json": {
+        "sha256": "94c00f2bccbdbf4891a1ed8be371e59debaedd03d64f5e8313cedfa4c60da22b",
+        "size": 260
+      },
+      "special_tokens_map.json": {
+        "sha256": "50eb73d51191696209d30d42d6ede50e57e7a542ca1db12df714b2c0aa3da8e2",
+        "size": 85
+      },
+      "tokenizer_config.json": {
+        "sha256": "573f3d46704a5482552885e2ca828fdcb2df1fbe90059a4d18ac2ee15820ca31",
+        "size": 181
+      },
+      "vocab.json": {
+        "sha256": "6641ad4761f75bbba7ca2591b1eaef57d1ab444762bf6a51f2ddbd70bfe3ee2f",
+        "size": 351
+      }
+    }
+  },
+  "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": 38,
+    "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": 9.5367431640625e-06,
+    "frame_argmax_agreement_int8": 1.0,
+    "fp32_size": 1262344939,
+    "int8_size": 356292447,
+    "frames": 49,
+    "runtime": {
+      "1.30.0": {
+        "provider": "CPUExecutionProvider",
+        "runs": {
+          "0.5": {
+            "samples": 8000,
+            "shape": [
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+              24,
+              38
+            ],
+            "seconds": 0.068863
+          },
+          "60.0": {
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+            "shape": [
+              1,
+              2999,
+              38
+            ],
+            "seconds": 8.79375
+          }
+        }
+      },
+      "1.23.2": {
+        "provider": "CPUExecutionProvider",
+        "runs": {
+          "0.5": {
+            "samples": 8000,
+            "shape": [
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+            "seconds": 0.038666
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+            "shape": [
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+            ],
+            "seconds": 8.017262
+          }
+        }
+      }
+    },
+    "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": 6.663475,
+      "peak_rss_bytes": 2870992896
+    },
+    "synthetic_sentence": {
+      "voice": "tr",
+      "caption": "merhaba dunya",
+      "samples": 21091,
+      "note": "pipeline/monotonicity check only; not an accuracy claim"
+    }
+  },
+  "files": {
+    "model.int8.onnx": {
+      "sha256": "6ba1e92e5bdeb2d9b4c23d555728f18313c89fe630bf9c55f9d0e09a62c87c74",
+      "size": 356292447
+    }
+  },
+  "elapsed_seconds": 40.235
+}

model.int8.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6ba1e92e5bdeb2d9b4c23d555728f18313c89fe630bf9c55f9d0e09a62c87c74
+size 356292447

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "feature_extractor_type": "Wav2Vec2FeatureExtractor",
+  "processor_class": "Wav2Vec2ProcessorWithLM",
+  "feature_size": 1,
+  "padding_side": "right",
+  "padding_value": 0,
+  "return_attention_mask": true,
+  "sampling_rate": 16000
+}

vocab.json

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+{"[PAD]": 0, "<s>": 1, "</s>": 2, "[UNK]": 3, "|": 4, "'": 5, "a": 6, "b": 7, "c": 8, "d": 9, "e": 10, "f": 11, "g": 12, "h": 13, "i": 14, "j": 15, "k": 16, "l": 17, "m": 18, "n": 19, "o": 20, "p": 21, "q": 22, "r": 23, "s": 24, "t": 25, "u": 26, "v": 27, "w": 28, "x": 29, "y": 30, "z": 31, "ç": 32, "ö": 33, "ü": 34, "ğ": 35, "ı": 36, "ş": 37}