---
license: cc-by-4.0
language:
- ko
tags:
- generation
---
## Model Details
* Model Description: Speech style converter model based on gogamza/kobart-base-v2
* Developed by: Juhwan, Lee and Jisu, Kim, TakSung Heo, and Minsu Jeong
* Model Type: Text-generation
* Language: Korean
* License: CC-BY-4.0

## Dataset
* [korean SmileStyle Dataset](https://github.com/smilegate-ai/korean_smile_style_dataset)
* Randomly split train/valid dataset (9:1)

## BLEU Score
* 25.35

## Uses
This model can be used for convert speech style
* formal: 문어체
* informal: 구어체
* android: 안드로이드
* azae: 아재
* chat: 채팅
* choding: 초등학생
* emoticon: 이모티콘
* enfp: enfp
* gentle: 신사
* halbae: 할아버지
* halmae: 할머니
* joongding: 중학생
* king: 왕
* naruto: 나루토
* seonbi: 선비
* sosim: 소심한
* translator: 번역기

```python

from transformers import pipeline

model = "KoJLabs/bart-speech-style-converter"
tokenizer = AutoTokenizer.from_pretrained(model)

nlg_pipeline = pipeline('text2text-generation',model=model, tokenizer=tokenizer)
styles = ["문어체", "구어체", "안드로이드", "아재", "채팅", "초등학생", "이모티콘", "enfp", "신사", "할아버지", "할머니", "중학생", "왕", "나루토", "선비", "소심한", "번역기"]

for style in styles:
    text = f"{style} 형식으로 변환:오늘은 닭볶음탕을 먹었다. 맛있었다."
    out = nlg_pipeline(text, max_length=100)
    print(style, out[0]['generated_text'])
```

## Model Source
https://github.com/KoJLabs/speech-style/tree/main

## Speech style conversion package
You can exercise korean speech style conversion task with python package [KoTAN](https://github.com/KoJLabs/KoTAN)