178 citations · 430 across the 13 of their papers we have counts for
13 papers
Seed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognition
Ye Bai, Jingping Chen, Jitong Chen +52
Modern automatic speech recognition (ASR) model is required to accurately transcribe diverse speech signals (from different domains, languages, accents, etc) given the specific con…
Seed-TTS: A Family of High-Quality Versatile Speech Generation Models
Philip Anastassiou, Jiawei Chen, Jitong Chen +43
We introduce Seed-TTS, a family of large-scale autoregressive text-to-speech (TTS) models capable of generating speech that is virtually indistinguishable from human speech. Seed-T…
StemGen: A music generation model that listens
Julian D. Parker, Janne Spijkervet, Katerina Kosta +6
End-to-end generation of musical audio using deep learning techniques has seen an explosion of activity recently. However, most models concentrate on generating fully mixed music i…
InstructME: An Instruction Guided Music Edit And Remix Framework with Latent Diffusion Models
Bing Han, Junyu Dai, Weituo Hao +6
Music editing primarily entails the modification of instrument tracks or remixing in the whole, which offers a novel reinterpretation of the original piece through a series of oper…
Efficient Neural Music Generation
Max W. Y. Lam, Qiao Tian, Tang Li +10
Recent progress in music generation has been remarkably advanced by the state-of-the-art MusicLM, which comprises a hierarchy of three LMs, respectively, for semantic, coarse acous…
Differentiable Wavetable Synthesis
Siyuan Shan, Lamtharn Hantrakul, Jitong Chen +2
Differentiable Wavetable Synthesis (DWTS) is a technique for neural audio synthesis which learns a dictionary of one-period waveforms i.e. wavetables, through end-to-end training.…