Chinese Lens vs ChatTTS - Text to Speech使用状況と統計

Chinese Lens provides quick scanning of Chinese text images and converting them into text copies. It also takes dictations of Chinese speaking and convert them into Simplified or Traditional text based on settings configured by users. Texts can be merged for organization purpose and for sharing. The app is also a tool for the students of the Chinese language. It provides a text analysis tool that breaks the paragraphs into sentences and words, with pinyin and dictionary explanations conveniently displayed for easier learning.
  • Apple App ストア
  • 無料
  • ユーティリティ

ストアランキング

- -

ChatTTS is a speech generation model designed for conversational scenarios, especially for conversational tasks of Large Language Model (LLM) assistants, as well as applications such as conversational audio and video introductions. It supports Chinese and English, and by training with approximately 100,000 hours of Chinese and English data, ChatTTS demonstrates high quality and naturalness in speech synthesis. ChatTTS can be used for a variety of applications, including but not limited to: Conversational tasks of Large Language Model assistants Conversational speech generation Video introductions Educational and training content speech synthesis Any application or service that requires text-to-speech capabilities ChatTTS is trained with approximately 100,000 hours of Chinese and English data. The dataset includes a variety of spoken content, helping the model learn to generate natural and high-quality speech. The diversity and quantity of training data ensure that ChatTTS can effectively handle a variety of speech synthesis tasks.
  • Apple App ストア
  • 無料
  • ユーティリティ

ストアランキング

- -

Chinese Lens対ChatTTS - Text to Speechランキング比較

と過去28日間の Chinese Lens ランキング傾向を比較 ChatTTS - Text to Speech

ランキング

ご利用可能なデータがありません

Chinese Lens 対 ChatTTS - Text to Speech 国の比較によるランキング

と過去28日間の Chinese Lens ランキング傾向を比較 ChatTTS - Text to Speech

表示できるデータはありません

無料トライアルで任意のサイトと比較する

始める
Chinese Lens VS.
ChatTTS - Text to Speech

1月 9, 2025