There are examples of speech sample recordings and synthesized speech based on different numbers of samples. The synthesized speech had some noise distortion but the samples did sound like the original speakers.
Baidu attempted to learn speaker characteristics from only a few utterances (i.e., sentences of few seconds duration). This problem is commonly known as "voice cloning." Voice cloning is expected to have significant applications in the direction of personalization in human-machine interfaces.
They tried two fundamental approaches for solving the problems with voice cloning: speaker adaptation and speaker encoding.
Speaker adaptation is based on fine-tuning a multi-speaker generative model with a few cloning samples, by using backpropagation-based optimization. Adaptation can be applied to the whole model, or only the low-dimensional speaker embeddings. The latter enables a much lower number of parameters to represent each speaker, albeit it yields a longer cloning time and lower audio quality.