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LICENSES/CORAL-LICENSE

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+LICENSED MATERIAL (INCLUDING DATA) - LICENSE TO USE
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+The Licensed Material (as defined below) is made available to You by Alexandra
+Instituttet A/S, Åbogade 34, 8200 Aarhus N, Denmark and may be utilised solely in
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+following additions:
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+1.	The license is governed by the laws of the Kingdom of Denmark
+2.	Any dispute arising out of or in connection herewith, including any disputes
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+ 
+
+CONDITIONS
+
+Section I: PREAMBLE
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+These Conditions are based on OpenRAIL-M License adopted to fit the licensing of Data. A
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+Section III: CONDITIONS OF USAGE, DISTRIBUTION AND REDISTRIBUTION
+
+3. Distribution and Redistribution. You may host for Third Party remote access purposes
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+    (a) Use-based restrictions in paragraph 4 MUST be included as an enforceable
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+4. Use-based restrictions. The restrictions set forth in Attachment A are considered
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+Section IV: OTHER PROVISIONS
+
+6. Updates and Runtime Restrictions. To the maximum extent permitted by law, Licensor
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+11. If any provision of this License is held to be invalid, illegal or unenforceable,
+    the remaining provisions shall be unaffected thereby and remain valid as if such
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+
+END OF TERMS AND CONDITIONS
+
+
+Attachment A
+
+USE RESTRICTIONS
+
+You agree not to use the Licensed Material or the Adapted Material in any of the
+following ways:
+
+1. Legal:
+    (a) In any way that violates any applicable national, federal, state, local or
+        international law or regulation.
+2. Harm and Discrimination
+    (a) For the purpose of exploiting, Harming or attempting to exploit or Harm minors
+        in any way;
+    (b) To generate or disseminate false information with the purpose of Harming others;
+    (c) To generate or disseminate personal identifiable information that can be used to
+        Harm an individual;
+    (d) To defame, disparage or otherwise harass others;
+    (e) For any use intended to or which has the effect of Harming individuals or groups
+        based on online or offline social behavior or known or predicted personal or
+        personality characteristics
+    (f) To exploit any of the vulnerabilities of a specific group of persons based on
+        their age, social, physical or mental characteristics, in order to materially
+        distort the behavior of a person belonging to that group in a manner that causes
+        or is likely to cause that person or another person Harm
+    (g) For any use intended to or which has the effect of discriminating against
+        individuals or groups based on legally protected characteristics or categories.
+3. Transparency
+    (a) To generate or disseminate machine-generated information or content in any
+        medium without expressly and intelligibly disclaiming that it is
+        machine-generated;
+    (b) To impersonate or attempt to impersonate human beings for purposes of deception;
+    (c) For fully automated decision making that adversely impacts an individual’s legal
+        rights or otherwise creates or modifies a binding, enforceable obligation.

LICENSES/FTSPEECH-LICENSE.md

@@ -0,0 +1,8 @@
+---
+layout: page
+title: License
+---
+<br>
+2020, **FT Speech**, [ftspeech.dk](ftspeech.dk)
+
+Any use of FT Speech text and audio data must be in accordance with the following two licenses: [Folketing's open data](https://www.ft.dk/da/dokumenter/aabne_data#290AB29F56C54AC88474BC53393A3AE0) and [Folketing TV](https://www.ft.dk/da/aktuelt/tv-fra-folketinget/deling-og-rettigheder). The data released here must always be accompanied by this LICENSE statement and the two Folketing licenses.

MODEL_LICENSE.md

@@ -0,0 +1,23 @@
+# Ekko v1 Tiny model terms
+
+Ekko v1 Tiny is a Derivative Model of `nvidia/parakeet-rnnt-110m-da-dk` and is
+subject to the NVIDIA Open Model License. The official agreement is included at
+`LICENSES/NVIDIA-OPEN-MODEL-LICENSE.pdf`, and the required NVIDIA attribution is
+in `NOTICE`.
+
+RyeAI applies Creative Commons Attribution 4.0 International to the
+modifications it has the right to license. A copy is included at
+`LICENSES/CC-BY-4.0.txt`. This does not replace the NVIDIA agreement.
+
+The model was trained on CoRal data. The included `LICENSES/CORAL-LICENSE`
+defines models trained on the data as Adapted Material and requires its use
+restrictions and license copy to accompany distribution. Those restrictions
+apply in addition to the NVIDIA agreement.
+
+FT Speech was also used. Its source statement is included at
+`LICENSES/FTSPEECH-LICENSE.md` and points to the applicable Folketinget terms.
+The effect of those terms on redistributed trained weights must be approved
+before this repository is made public.
+
+See `README.md` for provenance, modifications, limitations, and attribution.
+This notice is not legal advice.

NOTICE

@@ -0,0 +1,8 @@
+Ekko v1 Tiny is derived from nvidia/parakeet-rnnt-110m-da-dk.
+
+Licensed by NVIDIA Corporation under the NVIDIA Open Model License.
+
+Modifications by RyeAI include Danish domain adaptation and quantized runtime
+artifacts. See the model card for training-data provenance, additional terms,
+and the official NVIDIA license. The agreement is included at
+`LICENSES/NVIDIA-OPEN-MODEL-LICENSE.pdf`.

README.md

@@ -0,0 +1,219 @@
+---
+language:
+- da
+license: other
+license_name: ekko-composite-model-terms
+license_link: https://huggingface.co/RyeAI/ekko-v1-tiny/blob/main/MODEL_LICENSE.md
+thumbnail: https://huggingface.co/RyeAI/ekko-v1-tiny/resolve/b138df85a0782af0b61a3318167dcd291f1e67b7/cover.png
+library_name: nemo
+pipeline_tag: automatic-speech-recognition
+base_model: nvidia/parakeet-rnnt-110m-da-dk
+base_model_relation: finetune
+datasets:
+- alexandrainst/nst-da
+- alexandrainst/ftspeech
+- alexandrainst/nota
+- CoRal-project/coral-v3
+tags:
+- automatic-speech-recognition
+- speech-recognition
+- speech-to-text
+- danish
+- danish-asr
+- offline
+- local-inference
+- cpu-inference
+- nemo
+- gguf
+- onnx
+- sherpa-onnx
+- rnnt
+- word-timestamps
+metrics:
+- wer
+model-index:
+- name: Ekko v1 Tiny
+  results:
+  - task:
+      type: automatic-speech-recognition
+    dataset:
+      name: CoRal conversation
+      type: CoRal-project/coral-v3
+      config: conversation
+      split: test
+    metrics:
+    - type: wer
+      value: 24.15
+  - task:
+      type: automatic-speech-recognition
+    dataset:
+      name: CoRal read aloud
+      type: CoRal-project/coral-v3
+      config: read_aloud
+      split: test
+    metrics:
+    - type: wer
+      value: 11.87
+  - task:
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 17 Danish
+      type: mozilla-foundation/common_voice_17_0
+      config: da
+      split: test
+    metrics:
+    - type: wer
+      value: 8.44
+  - task:
+      type: automatic-speech-recognition
+    dataset:
+      name: FLEURS Danish
+      type: google/fleurs
+      config: da_dk
+      split: test
+    metrics:
+    - type: wer
+      value: 9.75
+  - task:
+      type: automatic-speech-recognition
+    dataset:
+      name: FTSpeech
+      type: alexandrainst/ftspeech
+      split: test_balanced
+    metrics:
+    - type: wer
+      value: 7.62
+---
+
+![Ekko v1 Tiny — offline Danish speech recognition](cover.png)
+
+[Leaderboard](https://huggingface.co/spaces/RyeAI/danish-asr-leaderboard) ·
+[Benchmark data](https://huggingface.co/datasets/RyeAI/danish-asr-leaderboard) ·
+[Evaluation harness](https://github.com/Rye-A1/danish-asr-leaderboard)
+
+# Ekko v1 Tiny — Offline Danish Speech-to-Text with Word Timestamps
+
+Ekko v1 Tiny is a compact, 110M-parameter Danish speech recognition model with
+word timestamps. It is a FastConformer RNN-T fine-tuned from
+`nvidia/parakeet-rnnt-110m-da-dk` and runs locally. Its raw output is lowercase
+text; pair it with `RyeAI/ekko-pnc` for capitalization and punctuation.
+
+## Benchmark
+
+**12.37% mean WER** across 26,780 rows from five Danish test sets, evaluated
+with the leaderboard harness at commit `6257737`. Scores use
+the published defaults: NFKC normalization, spoken-number folding, Danish
+number-word normalization, lowercase, punctuation removal, symmetric filler
+removal, and whitespace collapse. Lower is better.
+
+| Test set | Speech type | WER |
+|---|---|---:|
+| CoRal conversation | Spontaneous conversation | 24.15% |
+| CoRal read aloud | Read speech | 11.87% |
+| Common Voice 17 | Crowd-sourced read speech | 8.44% |
+| FLEURS `da_dk` | Read news-style speech | 9.75% |
+| FTSpeech | Parliamentary speech | 7.62% |
+| **Equal-weight mean** | | **12.37%** |
+
+The NeMo checkpoint processed the benchmark at **795.8x realtime** on one A100.
+The official run saved raw per-sample outputs, and an independent offline
+rescore reproduced 12.37% exactly.
+
+### Native GGUF quantization
+
+The F32, F16, Q8_0, Q6_K, Q5_K, Q5_0, Q4_K, and Q4_0 files are
+scored on the same current 26,780-row matrix and normalization policy as the
+NeMo result above. All 40 variant/domain outputs completed and passed exact-row
+offline scoring.
+
+| Variant | Size | Mean WER | CPU speed |
+|---|---:|---:|---:|
+| **F16** | 248.2 MiB | **12.315%** | 74.4x |
+| F32 | 430.6 MiB | 12.318% | 71.8x |
+| **Q8_0** | 162.7 MiB | **12.323%** | **74.9x** |
+| Q6_K | 141.8 MiB | 12.325% | 63.0x |
+| Q5_K | 129.8 MiB | 12.337% | 60.1x |
+| **Q5_0** | **128.5 MiB** | **12.370%** | **69.4x** |
+| Q4_K | 118.4 MiB | 12.442% | 65.4x |
+| Q4_0 | 117.1 MiB | 12.467% | 72.1x |
+
+Q5_0 remains the packaged default: it is 128.5 MiB, runs at 69.4x realtime,
+and is 0.047 mean-WER points behind Q8_0. Choose Q8_0 when the extra 34.2 MiB
+is acceptable and maximum quantized accuracy is preferred. F16 is the native
+reference tier.
+
+The matrix uses leaderboard commit `6257737` and normalizer SHA-256
+`90fb9d8985f5919dffdb969a54cdd0f858f63d99fa6c0783921966a785f62c39`.
+The saved filler-normalized score report has SHA-256
+`46fd3394b52a0a330ba3f8bb318417fdabe9ee7a1fa51358009299ebba661a31`.
+
+### ONNX and browser export
+
+The model is available for sherpa-onnx and was evaluated on the same 26,780-row
+matrix with mandatory non-silent peak normalization to 0.95. The browser
+downloads the compact int8 export.
+
+| Export | Size | Mean WER | CPU speed |
+|---|---:|---:|---:|
+| FP32 ONNX | 450.6 MiB | 12.465% | 53.4x |
+| **INT8 ONNX** | **129.0 MiB** | **12.946%** | **49.2x** |
+
+Both exports completed all five domains with zero runtime failures. INT8 is
+71.4% smaller than FP32 and trades 0.481 mean-WER points for the smaller browser
+download. The filler-normalized ONNX score report has SHA-256
+`e26343000384349a721da11fe316136b92fb87ffa78cb19133b6cb7193831155`.
+
+## Artifacts
+
+The current NeMo, GGUF, and ONNX artifacts are pinned at Hub revision
+`b138df85a0782af0b61a3318167dcd291f1e67b7` and verified by SHA-256.
+
+Clean-cache packaged download and inference tests passed on macOS arm64 and
+Linux x64 with native word timestamps. The Windows x64 artifact is mapped but
+has not been exercised against this release.
+
+| Format | Path | Measured mean WER |
+|---|---|---:|
+| NeMo | `ekko-v1-tiny.nemo` | 12.37% |
+| parakeet.cpp GGUF | `gguf-parakeet.cpp/ekko-v1-tiny-{f32,f16,q8_0,q6_k,q5_k,q5_0,q4_k,q4_0}.gguf` | 12.315-12.467% |
+| sherpa-onnx FP32 | `onnx-sherpa/{encoder,decoder,joiner}.onnx` | 12.465% |
+| sherpa-onnx INT8 | `onnx-sherpa/{encoder,decoder,joiner}.int8.onnx` | 12.946% |
+
+## Local Use
+
+```bash
+hf download RyeAI/ekko-v1-tiny \
+  gguf-parakeet.cpp/ekko-v1-tiny-q5_0.gguf \
+  --local-dir ./ekko-v1-tiny
+parakeet-cli transcribe \
+  --model ./ekko-v1-tiny/gguf-parakeet.cpp/ekko-v1-tiny-q5_0.gguf \
+  --input audio.wav --timestamps
+```
+
+NeMo usage:
+
+```python
+from nemo.collections.asr.models import EncDecRNNTBPEModel
+
+model = EncDecRNNTBPEModel.from_pretrained("RyeAI/ekko-v1-tiny")
+transcript = model.transcribe(["audio.wav"])[0]
+print(transcript.text)
+```
+
+## Training and limitations
+
+Ekko v1 Tiny trained for 50,000 steps on an 879,083-row,
+1,549.6-hour Danish manifest, including 454.1 hours of quality-gated
+pseudo-labelled audio.
+
+- Danish only.
+- Raw output has no punctuation or capitalization.
+- The 44-token vocabulary does not contain uppercase or punctuation tokens.
+- Punctuation and capitalization require a separate restoration model such as
+  `RyeAI/ekko-pnc`.
+- Spontaneous conversation remains the hardest benchmark domain.
+
+## License
+
+The complete model and data terms are documented in
+[`MODEL_LICENSE.md`](MODEL_LICENSE.md) and the bundled `LICENSES/` files.

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onnx-sherpa/SHA256SUMS

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+e26343000384349a721da11fe316136b92fb87ffa78cb19133b6cb7193831155  benchmark/scores-current-fillers.json

onnx-sherpa/benchmark/scores-current-fillers.json

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