README.md

metadata

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

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:

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.