I want to create a solution, which clones my voice. I tried my commercial solutions or implementation of Tacotron. Unfortunately, results not sound natural, generated voice sounds like a robot. Anybody could recommend good alternative?
The reason for robot like speech may be because tacotron uses griffin lim for vocoder, which cannot reproduce sound with perfection, often introducing robot like sound artifects.
A vocoder is a network that transforms a transform a spectrogram image back to speech waveform. Tacotron and many other speech generation neural network uses CNN to generate spectrogram instead of raw waveforms as output. Spectrogram is a lossy representation of raw audio waveform, so a perfect reconstruction of audio waveform is not possible. Griffin-Lim is a vocoder that uses algorithmic way to transform spectrogram to audio waveform, but often introduces a robot-like quality to generated waveforms. A neural network based vocoder can solve the problem. The wavenet vocoder is often used in speech generation as it can transform the spectrogram to audio with little artifects. Many new speech generation models use the wavenet vocoder as the deafult vocoder of the generation model. For a public implementation, this is a good github repository: https://github.com/r9y9/wavenet_vocoder
You can also use the newer tacotron 2 which uses the wavenet vocoder as the default vocoder. You can check it out here: https://github.com/Rayhane-mamah/Tacotron-2