Chenlin Liu

Mitigating Hallucinations in LM-Based TTS Models via Distribution Alignment Using GFlowNets

Language Model (LM)-based Text-to-Speech (TTS) systems often generate hallucinated speech that deviates from input text. Existing mitigation strategies either demand excessive training resources or introduce significant inference latency. In this paper, we propose GFlOwNet-guided distribution Alignm