FluentEditor2: Text-based Speech Editing by Modeling Multi-Scale Acoustic and Prosody Consistency

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Hauptverfasser: Liu, Rui, Xi, Jiatian, Jiang, Ziyue, Li, Haizhou
Format: Preprint
Veröffentlicht: 2024
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author Liu, Rui
Xi, Jiatian
Jiang, Ziyue
Li, Haizhou
author_facet Liu, Rui
Xi, Jiatian
Jiang, Ziyue
Li, Haizhou
contents Text-based speech editing (TSE) allows users to edit speech by modifying the corresponding text directly without altering the original recording. Current TSE techniques often focus on minimizing discrepancies between generated speech and reference within edited regions during training to achieve fluent TSE performance. However, the generated speech in the edited region should maintain acoustic and prosodic consistency with the unedited region and the original speech at both the local and global levels. To maintain speech fluency, we propose a new fluency speech editing scheme based on our previous \textit{FluentEditor} model, termed \textit{\textbf{FluentEditor2}}, by modeling the multi-scale acoustic and prosody consistency training criterion in TSE training. Specifically, for local acoustic consistency, we propose \textit{hierarchical local acoustic smoothness constraint} to align the acoustic properties of speech frames, phonemes, and words at the boundary between the generated speech in the edited region and the speech in the unedited region. For global prosody consistency, we propose \textit{contrastive global prosody consistency constraint} to keep the speech in the edited region consistent with the prosody of the original utterance. Extensive experiments on the VCTK and LibriTTS datasets show that \textit{FluentEditor2} surpasses existing neural networks-based TSE methods, including Editspeech, Campnet, A$^3$T, FluentSpeech, and our Fluenteditor, in both subjective and objective. Ablation studies further highlight the contributions of each module to the overall effectiveness of the system. Speech demos are available at: \url{https://github.com/Ai-S2-Lab/FluentEditor2}.
format Preprint
id arxiv_https___arxiv_org_abs_2410_03719
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle FluentEditor2: Text-based Speech Editing by Modeling Multi-Scale Acoustic and Prosody Consistency
Liu, Rui
Xi, Jiatian
Jiang, Ziyue
Li, Haizhou
Computation and Language
Sound
Audio and Speech Processing
Text-based speech editing (TSE) allows users to edit speech by modifying the corresponding text directly without altering the original recording. Current TSE techniques often focus on minimizing discrepancies between generated speech and reference within edited regions during training to achieve fluent TSE performance. However, the generated speech in the edited region should maintain acoustic and prosodic consistency with the unedited region and the original speech at both the local and global levels. To maintain speech fluency, we propose a new fluency speech editing scheme based on our previous \textit{FluentEditor} model, termed \textit{\textbf{FluentEditor2}}, by modeling the multi-scale acoustic and prosody consistency training criterion in TSE training. Specifically, for local acoustic consistency, we propose \textit{hierarchical local acoustic smoothness constraint} to align the acoustic properties of speech frames, phonemes, and words at the boundary between the generated speech in the edited region and the speech in the unedited region. For global prosody consistency, we propose \textit{contrastive global prosody consistency constraint} to keep the speech in the edited region consistent with the prosody of the original utterance. Extensive experiments on the VCTK and LibriTTS datasets show that \textit{FluentEditor2} surpasses existing neural networks-based TSE methods, including Editspeech, Campnet, A$^3$T, FluentSpeech, and our Fluenteditor, in both subjective and objective. Ablation studies further highlight the contributions of each module to the overall effectiveness of the system. Speech demos are available at: \url{https://github.com/Ai-S2-Lab/FluentEditor2}.
title FluentEditor2: Text-based Speech Editing by Modeling Multi-Scale Acoustic and Prosody Consistency
topic Computation and Language
Sound
Audio and Speech Processing
url https://arxiv.org/abs/2410.03719