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This paper presents a simple yet effective method to achieve prosody transferfrom a reference speech signal to synthesized speech. The main idea is toincorporate well-known acoustic correlates of prosody such as pitch andloudness contours of the reference speech into a modern neural text-to-speech(TTS) synthesizer such as Tacotron2 (TC2). More specifically, a small set ofacoustic features are extracted from reference audio and then used to conditiona TC2 synthesizer. The trained model is evaluated using subjective listeningtests and a novel objective evaluation of prosody transfer is proposed.Listening tests show that the synthesized speech is rated as highly natural andthat prosody is successfully transferred from the reference speech signal tothe synthesized signal.

Prosody Transfer in Neural Text to Speech Using Global Pitch and Loudness Features