---
license: apache-2.0
language: en
library_name: transformers
pipeline_tag: automatic-speech-recognition
tags:
- whisper
- automatic-speech-recognition
- peft
- lora
- gc-lora
- switchboard
---

# Whisper-medium Switchboard (GC-LoRA)

Whisper-medium adapted to the **Switchboard** dataset with **GC-LoRA** (Gated Convolutional LoRA),
from the paper *"GC-LoRA: Gated Convolutional LoRA for Parameter-Efficient Acoustic Adaptation"* (Interspeech 2026).

- **Base model:** `openai/whisper-medium.en`
- **Method:** GC-LoRA adapter on the encoder attention output projections (rank 8, kernel 31, scaling 16)
- **Switchboard test WER:** **6.3%**
- **Code:** https://github.com/balaji1312/gc_lora

## Usage

The checkpoint bundles the frozen Whisper backbone together with the trained GC-LoRA adapter.
Loading requires the custom modeling code in the [gc_lora repository](https://github.com/balaji1312/gc_lora); see `src/bin/decode_asr.py`
there for loading and decoding.

## Citation

```bibtex
@inproceedings{shankar2026gclora,
  author    = {Shankar, Natarajan Balaji and Wang, Zilai and Zhang, Kaiyuan and Shi, Mohan and Alwan, Abeer},
  title     = {{GC-LoRA}: Gated Convolutional {LoRA} for Parameter-Efficient Acoustic Adaptation},
  booktitle = {Interspeech 2026},
  year      = {2026},
}
```