Skip to content
This repository has been archived by the owner on Sep 29, 2023. It is now read-only.

Latest commit

 

History

History
16 lines (14 loc) · 1.23 KB

synthesis.md

File metadata and controls

16 lines (14 loc) · 1.23 KB

Synthesising the voice

With trained model weights we can now implement the TTS app for our generated voice model.

Arguments

  • model_path: The path to your generated model
  • vocoder_model_path: The path to your vocoder model (default hifigan model found here)
  • hifigan_config_path: The path to your hifigan config (default higigan config found here)
  • text: Text you wish to synthesize
  • graph_output_path (optional): Path to save alignment graph to
  • audio_output_path (optional): Path to save generated audio to
  • silence_padding (optional) : Seconds of silence to seperate each clip by with multi-line synthesis (default is 0.15)
  • sample_rate (optional) : Audio sample rate (default is 22050)
  • max_decoder_steps (optional) : Max decoder steps controls sequence length and memory usage during inference. Increasing this will use more memory but may allow for longer sentences. (default is 1000)

How to run

python synthesize.py -m checkpoint_500000 -vm g_02500000 -hc config.json -t "Hello everyone, how are you?" -g graph.png -a audio.wav