arXiv:2504.20581
공식 코드 · Papers with Code
ClonEval: An Open Voice Cloning Benchmark
원문 초록
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.
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Few-Shot Speech Deepfake Detection Adaptation with Gaussian Processes
Spark-TTS: An Efficient LLM-Based Text-to-Speech Model with Single-Stream Decoupled Speech Tokens
IndexTTS: An Industrial-Level Controllable and Efficient Zero-Shot Text-To-Speech System
Lina-Speech: Gated Linear Attention is a Fast and Parameter-Efficient Learner for text-to-speech synthesis
EmoKnob: Enhance Voice Cloning with Fine-Grained Emotion Control
LlamaPartialSpoof: An LLM-Driven Fake Speech Dataset Simulating Disinformation Generation
토론
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