VITS 音声翻訳
The end-to-end TTS architecture that combines a variational autoencoder, normalizing flows, and adversarial training.
SSML タグでテキストを囲み、正確な制御を行う:
<speak><prosody rate="slow">Slow speech</prosody></speak>
選択したモデルが理解するタグ - クリックしてテキストにドラッグします:
このモデルは単純テキストを読み込み、インラインタグは無視されます。タグベースの感情を表現するには、Orpheus や Bark のような表現モデルに切り替えてください。
カスタム発音を定義 (単語=発音):
情報 VITS
VITS — Variational Inference with adversarial learning for end-to-end Text-to-Speech — was introduced by Jaehyeon Kim and collaborators in 2021 and became a foundational architecture for modern neural speech. Rather than the older two-stage pipeline, it synthesizes audio in a single parallel end-to-end pass, pairing a variational autoencoder with normalizing flows and a GAN-style adversarial training process to lift naturalness. At about 25M parameters and trained on ~585 hours, it produces natural prosody at fast inference speeds and supports multiple speakers. It serves as a solid general-purpose, free baseline and underpins many later models such as Piper and MeloTTS.
適合する: General-purpose text-to-speech with natural prosody
すべてブラウズ VITS 声概要
- 開発者
- Jaehyeon Kim et al.
- ライセンス
- MIT
- 動物
- free
- スピード
- fast
- 声のクローン
- いや
- 言語
- English, German, Spanish, French, Portuguese, Dutch, Finnish, Hungarian, Bulgarian, Japanese, Polish
- 最大文字数
- 2000