Transformer-TTS and TransformerTTS
These two projects are competitors, as both are independent PyTorch implementations of the "Neural Speech Synthesis with Transformer Network" paper, aiming to provide a non-autoregressive Transformer-based neural network for text-to-speech.
About Transformer-TTS
soobinseo/Transformer-TTS
A Pytorch Implementation of "Neural Speech Synthesis with Transformer Network"
Implements end-to-end mel-spectrogram synthesis using multi-head self-attention in both encoder and decoder, achieving 3-4x faster training than seq2seq baselines like Tacotron. Replaces the WaveNet vocoder with a CBHG-based postnet and Griffin-Lim vocoding for waveform reconstruction. Trained on LJSpeech with Noam-style learning rate scheduling and gradient clipping, with pretrained checkpoints available.
About TransformerTTS
spring-media/TransformerTTS
🤖💬 Transformer TTS: Implementation of a non-autoregressive Transformer based neural network for text to speech.
Built on TensorFlow 2, it combines a two-stage pipeline with an Aligner model for duration extraction and a Forward Transformer for parallel mel-spectrogram generation with controllable pitch prediction. Pre-trained LJSpeech weights integrate seamlessly with MelGAN and HiFiGAN vocoders for end-to-end synthesis, while the non-autoregressive approach eliminates repetition artifacts and enables real-time inference with speed/pitch modulation.
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