ClonEval: An Open Voice Cloning Benchmark
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Abstract (arXiv)
We present a novel benchmark for voice cloning text-to-speech models. The benchmark consists of an evaluation protocol, an open-source library for assessing the performance of voice cloning models, and an accompanying leaderboard. The paper discusses design considerations and presents a detailed description of the evaluation procedure. The usage of the software library is explained, along with the organization of results on the leaderboard.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 7 of its 23 references that are in the map. First posted on arXiv 29 Apr 2025.
Builds on
7 of 23 references.
References · 7
- 2021WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processingcited by 1,657
- 2024Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preferencecited by 1,184
- 2023Neural Codec Language Models are Zero-Shot Text to Speech Synthesizerscited by 752
- 2023Voicebox: Text-Guided Multilingual Universal Speech Generation at Scalecited by 379
- 2023Seamless: Multilingual Expressive and Streaming Speech Translationcited by 192
- 2021SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processingcited by 180
- 2023Speak Foreign Languages with Your Own Voice: Cross-Lingual Neural Codec Language Modelingcited by 167
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Citing papers per year: 2026: 1.
1 paper.