| --- |
| license: mit |
| library_name: onnx |
| tags: |
| - automatic-speech-recognition |
| - speech |
| - russian |
| - onnx |
| - rnnt |
| - gigaam |
| language: |
| - ru |
| base_model: |
| - ai-sage/GigaAM-v3 |
| --- |
| |
| # CoppersideASR |
|
|
| CoppersideASR is an ONNX RNN-T speech recognition model bundle for the |
| CopperASR runtime. The model is configured for Russian speech recognition and |
| 16 kHz audio input. |
|
|
| The repository uses a minimal normalized layout: three ONNX graphs, a token |
| mapping, and a runtime manifest. CopperASR can load this bundle directly without |
| additional conversion steps. |
|
|
| ## Files |
|
|
| - `encoder.onnx` |
| - `decoder.onnx` |
| - `joint.onnx` |
| - `tokens.txt` |
| - `model_manifest.json` |
|
|
| ## Runtime Contract |
|
|
| | File | Purpose | |
| | --- | --- | |
| | `encoder.onnx` | RNN-T acoustic encoder | |
| | `decoder.onnx` | RNN-T prediction network | |
| | `joint.onnx` | RNN-T joint network | |
| | `tokens.txt` | Token id mapping with `<blk>` at id `1024` | |
| | `model_manifest.json` | Runtime contract and checksums | |
|
|
| ## Usage with CopperASR |
|
|
| ```python |
| from copper_asr import CopperASR |
| |
| asr = CopperASR(model_source="copperside-gigaam-v3-e2e-rnnt") |
| result = asr.transcribe("audio.wav") |
| print(result.full_text) |
| ``` |
|
|
| For a local checkout: |
|
|
| ```python |
| asr = CopperASR( |
| model_source="copperside-gigaam-v3-e2e-rnnt", |
| model_path="path/to/CoppersideASR", |
| ) |
| ``` |
|
|
| ## Model Details |
|
|
| The model uses an RNN-T layout with separate encoder, decoder, and joint ONNX |
| graphs. Tokenizer settings, feature extraction parameters, decoder limits, and |
| file checksums are recorded in `model_manifest.json`. |
|
|
