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Sequence expansion between encoder and decoder is a critical challenge insequence-to-sequence TTS. Attention-based methods achieve great naturalness butsuffer from unstable issues like missing and repeating phonemes, not to mentionaccurate duration control. Duration-informed methods, on the contrary, seem toeasily adjust phoneme duration but show obvious degradation in speechnaturalness. This paper proposes PAMA-TTS to address the problem. It takes theadvantage of both flexible attention and explicit duration models. Based on themonotonic attention mechanism, PAMA-TTS also leverages token duration andrelative position of a frame, especially countdown information, i.e. in howmany future frames the present phoneme will end. They help the attention tomove forward along the token sequence in a soft but reliable control.Experimental results prove that PAMA-TTS achieves the highest naturalness,while has on-par or even better duration controllability than theduration-informed model.

PAMA-TTS: Progression-Aware Monotonic Attention for Stable Seq2Seq TTS With Accurate Phoneme Duration Control