Gigaam v3 Onnx Ru

--- language: ru license: mit tags: - speech-recognition - russian - gigaam - onnx - conformer - rnnt metrics: - cer library: onnxruntime pipeline_tag: automatic-speech-recognition --- # GigaAM-v3 ONNX — Russian Speech Recognition GigaAM-v3 (222.5M params) exported to ONNX with Int8 quantization. CER ~4-5%, RTF ~0.04 on CPU (25× faster than real time). ## Quick Start ```bash pip install onnxruntime numpy torch torchaudio soundfile pandas python3 recognize.py speech.wav ``` Result: `"В древнем Китае использовали уникальный способ обозначения периодов времени."` Знаки препинания (заглавные буквы, запятые, точки) восстанавливаются автоматически через Silero TE model (скачивается при первом запуске). Без пунктуации: `--no-punct` ## Model Files | File | Size | Description | |------|------|-------------| | `model/gigaam_v3_rnnt_encoder.onnx` | 305 MB | Conformer encoder (Int8) | | `model/gigaam_v3_rnnt_decoder.onnx` | 3.2 MB | LSTM decoder | | `model/gigaam_v3_rnnt_joint.onnx` | 1.4 MB | Joint network | | `model/gigaam_v3_rnnt_tokens.txt` | 195 B | Token vocabulary (33 chars + blank) | ## Architecture - **Encoder**: Conformer 16 layers, 768 dim (222M params) - **Decoder**: LSTM 1 layer, 320 dim + Embedding (34→320) - **Joint**: 2× Linear(768→320, 320→320) + ReLU + Linear(320→34) - **Vocabulary**: 33 Russian letters + space + `<blk>` ## Performance | Metric | Value | |--------|-------| | Params | 222.5M | | CER (test set) | ~4.9% | | RTF (CPU, FP32) | 0.04 | | RTF (CPU, Int8) | 0.03 | | Avg decode (12s audio) | ~450 ms (FP32) / ~320 ms (Int8) | ## Usage ### Command Line ```bash # Recognize a WAV file (16kHz, mono) python3 recognize.py speech.wav # Benchmark python3 recognize.py --benchmark ``` ### Python API ```python from recognize import GigaAMRecognizer asr = GigaAMRecognizer('model') # From file text = asr.transcribe('speech.wav') # From numpy array (16kHz, mono) import soundfile as sf audio, sr = sf.read('speech.wav') text = asr.transcribe_raw(audio) print(text) # "эта идея пришла из китая где излюбленным цветком был цвет сливы" ``` ### GUI (offline ASR app) ```bash python3 asr_gui.py ``` Buttons: 🎤 Start / ⏹ Stop. Text is copied to clipboard automatically. ## Requirements - Python 3.10+ - `onnxruntime` (or `onnxruntime-gpu` for GPU) - `numpy` - `torch`, `torchaudio` (for mel spectrogram) - `soundfile` - `pandas` (optional, for...

Source context: 0 downloads · 0 likes · Pipeline automatic-speech-recognition · Repo Dimitrius174/gigaam-v3-onnx-ru