Convert text to speech with voice cloning and emotional adaptation.
npx skills add https://github.com/anbeime/skill --skill tts-voice-synthesis
Please help me install this Agent Skill. Skill: tts-voice-synthesis Source: https://github.com/anbeime/skill/tree/main/skills/tts-voice-synthesis Command: npx skills add https://github.com/anbeime/skill --skill tts-voice-synthesis
This Skill transforms written text into natural-sounding speech, offering advanced features like voice cloning, emotional adaptation, and real-time streaming.
Use the tts-voice-synthesis skill to convert the text 'Hello, world!' into an audio file named 'output.wav'.
High-intent search queries and answers about installing and using this skill.
Text-to-speech synthesis transforms written text into natural audio by leveraging models like Fish-Speech, ChatTTS, and CosyVoice to generate speech with specific emotional tones such as happy, sad, or angry.
Yes, voice cloning creates custom voices from short audio samples using PyTorch and transformers. It synthesizes new speech matching the original speaker's characteristics for Chinese, English, or Cantonese text.
Real-time audio streaming produces audio incrementally using torchaudio and librosa. This enables interactive applications to generate and play speech chunks immediately without waiting for the entire text to process.
Generating speech from text requires PyTorch, torchaudio, transformers, scipy, numpy, librosa, soundfile, and pydub. These libraries handle deep learning inference, audio processing, and output file creation.
The best way to create Chinese and Cantonese voiceovers is using multi-language text-to-speech synthesis with CosyVoice or ChatTTS, outputting high-quality WAV files via the soundfile library.
Voice cloning limitations depend on the input audio quality and length provided to the transformers models. While short samples work, clear audio yields better custom voice synthesis results for text-to-speech.
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