title: Incremental FastPitch: Chunk-based High Quality Text to Speech
summary: Parallel text-to-speech models have been widely applied for real-time speech
  synthesis, and they offer more controllability and a much faster synthesis
  process compared with conventional auto-regressive models. Although parallel
  models have benefits in many aspects, they become naturally unfit for
  incremental synthesis due to their fully parallel architecture such as
  transformer. In this work, we propose Incremental FastPitch, a novel FastPitch
  variant capable of incrementally producing high-quality Mel chunks by improving
  the architecture with chunk-based FFT blocks, training with receptive-field
  constrained chunk attention masks, and inference with fixed size past model
  states. Experimental results show that our proposal can produce speech quality
  comparable to the parallel FastPitch, with a significant lower latency that
  allows even lower response time for real-time speech applications.
paper_authors._id: 65962c9f25b1c7a91068f44b
paper_authors.name: Muyang Du
paper_authors._id: 65962c9f25b1c7a91068f44c
paper_authors.name: Chuan Liu
paper_authors._id: 65962c9f25b1c7a91068f44d
paper_authors.name: Junjie Lai
paper_title: Incremental FastPitch: Chunk-based High Quality Text to Speech
paper_summary: Parallel text-to-speech models have been widely applied for real-time speech
  synthesis, and they offer more controllability and a much faster synthesis
  process compared with conventional auto-regressive models. Although parallel
  models have benefits in many aspects, they become naturally unfit for
  incremental synthesis due to their fully parallel architecture such as
  transformer. In this work, we propose Incremental FastPitch, a novel FastPitch
  variant capable of incrementally producing high-quality Mel chunks by improving
  the architecture with chunk-based FFT blocks, training with receptive-field
  constrained chunk attention masks, and inference with fixed size past model
  states. Experimental results show that our proposal can produce speech quality
  comparable to the parallel FastPitch, with a significant lower latency that
  allows even lower response time for real-time speech applications.
paper_ai_keywords: FastPitch Mel chunks FFT blocks chunk attention masks past model states