Fish Speech: Open source text-to-speech synthesis
Transformer-based TTS with voice cloning from reference audio.
Learn more about Fish Speech
Fish Speech is an open-source text-to-speech synthesis system that generates natural speech audio from text input using transformer-based neural network architectures. The system implements voice cloning capabilities by analyzing reference audio samples to extract speaker characteristics, which are then applied during the synthesis process to reproduce the target voice. It processes text through multiple stages including linguistic analysis, acoustic feature prediction, and neural vocoding to produce waveform output. The architecture separates the text-to-acoustic-feature generation from the vocoding stage, allowing for modular optimization of each component in the speech synthesis pipeline.
Transformer-based architecture
Uses transformer models for semantic token prediction combined with VQVAE quantization, enabling efficient discrete representation of speech content.
Emotional speech control
Supports multiple emotional markers and tone specifications during synthesis, allowing fine-grained control over prosody and expression in generated speech.
Voice cloning from samples
Enables speaker adaptation through reference audio input, allowing synthesis in arbitrary speaker voices without requiring extensive speaker-specific training data.
from fish_speech import TextToSpeech
tts = TextToSpeech()
audio = tts.synthesize("Hello, this is a test of Fish Speech synthesis.")
audio.save("output.wav")Top in AI & ML
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