arXiv:2503.03250
Good practices for evaluation of synthesized speech
원문 초록
This document is provided as a guideline for reviewers of papers about speech synthesis. We outline some best practices and common pitfalls for papers about speech synthesis, with a particular focus on evaluation. We also recommend that reviewers check the guidelines for authors written in the paper kit and consider those as reviewing criteria as well. This is intended to be a living document, and it will be updated as we receive comments and feedback from readers. We note that this document is meant to provide guidance only, and that reviewers should ultimately use their own discretion when evaluating papers.
함께 살펴볼 논문
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DeepGesture: A conversational gesture synthesis system based on emotions and semantics
RapFlow-TTS: Rapid and High-Fidelity Text-to-Speech with Improved Consistency Flow Matching
InstructTTSEval: Benchmarking Complex Natural-Language Instruction Following in Text-to-Speech Systems
Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models
ZipVoice: Fast and High-Quality Zero-Shot Text-to-Speech with Flow Matching
OmniDRCA: Parallel Speech-Text Foundation Model via Dual-Resolution Speech Representations and Contrastive Alignment
토론
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