---
license: apache-2.0
language:
- zh
- aa
- af
metrics:
- accuracy
library_name: diffusers
pipeline_tag: text-to-image
tags:
- medical
- code
- suibian
---

# Whisper

Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. Trained on 680k hours 
of labelled data, Whisper models demonstrate a strong ability to generalise to many datasets and domains **without** the need 
for fine-tuning.

Whisper was proposed in the paper [Robust Speech Recognition via Large-Scale Weak Supervision](https://arxiv.org/abs/2212.04356) 
by Alec Radford et al. from OpenAI. The original code repository can be found [here](https://github.com/openai/whisper).

Whisper `large-v3` has the same architecture as the previous large models except the following minor differences:

1. The input uses 128 Mel frequency bins instead of 80
2. A new language token for Cantonese