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Text-To-Speech Synthesis
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 6
- 보존된 평가 기록
- 21
Text-To-Speech Synthesis is a machine learning task that involves converting written text into spoken words. The goal is to generate synthetic speech that sounds natural and resembles human speech as closely as possible.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yanggeng1995/GAN-TTS
https://github.com/yangyucheng000/University/tree/main/model-2/fastspeech2_conformer
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
https://github.com/yoshifumi-nakano/visual-text-to-speech
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
https://github.com/zhangbo2008/fastSpeeck2_chinese_train
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.