  In this paper, we propose a method of speaker adaption with intuitive
prosodic features for statistical parametric speech synthesis. The intuitive
prosodic features employed in this method include pitch, pitch range, speech
rate and energy considering that they are directly related with the overall
prosodic characteristics of different speakers. The intuitive prosodic features
are extracted at utterance-level or speaker-level, and are further integrated
into the existing speaker-encoding-based and speaker-embedding-based adaptation
frameworks respectively. The acoustic models are sequence-to-sequence ones
based on Tacotron2. Intuitive prosodic features are concatenated with text
encoder outputs and speaker vectors for decoding acoustic features.Experimental
results have demonstrated that our proposed methods can achieve better
objective and subjective performance than the baseline methods without
intuitive prosodic features. Besides, the proposed speaker adaption method with
utterance-level prosodic features has achieved the best similarity of synthetic
speech among all compared methods.
