8 citations · 11 across the 3 of their papers we have counts for
5 papers · 1 filter
Autoregressive Speech Synthesis without Vector Quantization
Lingwei Meng, Long Zhou, Shujie Liu +9
We present MELLE, a novel continuous-valued token based language modeling approach for text-to-speech synthesis (TTS). MELLE autoregressively generates continuous mel-spectrogram f…
VALL-E 2: Neural Codec Language Models are Human Parity Zero-Shot Text to Speech Synthesizers
Sanyuan Chen, Shujie Liu, Long Zhou +6
This paper introduces VALL-E 2, the latest advancement in neural codec language models that marks a milestone in zero-shot text-to-speech synthesis (TTS), achieving human parity fo…
VALL-E R: Robust and Efficient Zero-Shot Text-to-Speech Synthesis via Monotonic Alignment
Bing Han, Long Zhou, Shujie Liu +7
With the help of discrete neural audio codecs, large language models (LLM) have increasingly been recognized as a promising methodology for zero-shot Text-to-Speech (TTS) synthesis…
WavLLM: Towards Robust and Adaptive Speech Large Language Model
Shujie Hu, Long Zhou, Shujie Liu +9
The recent advancements in large language models (LLMs) have revolutionized the field of natural language processing, progressively broadening their scope to multimodal perception…
Boosting Large Language Model for Speech Synthesis: An Empirical Study
Hongkun Hao, Long Zhou, Shujie Liu +4
Large language models (LLMs) have made significant advancements in natural language processing and are concurrently extending the language ability to other modalities, such as spee…