most citedCLaM-TTS: Improving Neural Codec Language Model for Zero-Shot Text-to-Speech

2 citations · 3 across the 5 of their papers we have counts for

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eess.AS2024

DiTTo-TTS: Diffusion Transformers for Scalable Text-to-Speech without Domain-Specific Factors

Keon Lee, Dong Won Kim, Jaehyeon Kim +2

Large-scale latent diffusion models (LDMs) excel in content generation across various modalities, but their reliance on phonemes and durations in text-to-speech (TTS) limits scalab…

eess.AS2024★ 2 cited

CLaM-TTS: Improving Neural Codec Language Model for Zero-Shot Text-to-Speech

Jaehyeon Kim, Keon Lee, Seungjun Chung +1

With the emergence of neural audio codecs, which encode multiple streams of discrete tokens from audio, large language models have recently gained attention as a promising approach…