578 citations · 2.9k across the 69 of their papers we have counts for
70 papers
PromptTTS 2: Describing and Generating Voices with Text Prompt
Yichong Leng, Zhifang Guo, Kai Shen +12
Speech conveys more information than text, as the same word can be uttered in various voices to convey diverse information. Compared to traditional text-to-speech (TTS) methods rel…
EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Qingyan Guo, Rui Wang, Junliang Guo +6
Large Language Models (LLMs) excel in various tasks, but they rely on carefully crafted prompts that often demand substantial human effort. To automate this process, in this paper,…
Extract and Attend: Improving Entity Translation in Neural Machine Translation
Zixin Zeng, Rui Wang, Yichong Leng +4
While Neural Machine Translation(NMT) has achieved great progress in recent years, it still suffers from inaccurate translation of entities (e.g., person/organization name, locatio…
NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers
Kai Shen, Zeqian Ju, Xu Tan +6
Scaling text-to-speech (TTS) to large-scale, multi-speaker, and in-the-wild datasets is important to capture the diversity in human speech such as speaker identities, prosodies, an…
ResiDual: Transformer with Dual Residual Connections
Shufang Xie, Huishuai Zhang, Junliang Guo +6
Transformer networks have become the preferred architecture for many tasks due to their state-of-the-art performance. However, the optimal way to implement residual connections in…
CLaMP: Contrastive Language-Music Pre-training for Cross-Modal Symbolic Music Information Retrieval
Shangda Wu, Dingyao Yu, Xu Tan +1
We introduce CLaMP: Contrastive Language-Music Pre-training, which learns cross-modal representations between natural language and symbolic music using a music encoder and a text e…