NHNDQ/bart-speech-style-converter

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
• —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

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