Transformer-TTS
Discover a Pytorch-based model that provides quicker training durations in speech synthesis using the Transformer Network. This implementation offers comparative audio quality to traditional seq2seq models like Tacotron, with notably faster training times. By employing the CBHG model for post network learning and the Griffin-Lim algorithm for audio transformation, it leverages the LJSpeech dataset to effectively synthesize speech. This makes it a valuable resource for developers and researchers focused on enhancing performance while preserving quality.
