17 citations · 17 across the 5 of their papers we have counts for
6 papers
UniM: A Unified Any-to-Any Interleaved Multimodal Benchmark
Yanlin Li, Minghui Guo, Kaiwen Zhang +13
In real-world multimodal applications, systems usually need to comprehend arbitrarily combined and interleaved multimodal inputs from users, while also generating outputs in any in…
High Quality Audio Coding with MDCTNet
Grant Davidson, Mark Vinton, Per Ekstrand +3
We propose a neural audio generative model, MDCTNet, operating in the perceptually weighted domain of an adaptive modified discrete cosine transform (MDCT). The architecture of the…
Deep Performer: Score-to-Audio Music Performance Synthesis
Hao-Wen Dong, Cong Zhou, Taylor Berg-Kirkpatrick +1
Music performance synthesis aims to synthesize a musical score into a natural performance. In this paper, we borrow recent advances in text-to-speech synthesis and present the Deep…
Source coding of audio signals with a generative model
Roy Fejgin, Janusz Klejsa, Lars Villemoes +1
We consider source coding of audio signals with the help of a generative model. We use a construction where a waveform is first quantized, yielding a finite bitrate representation.…
High-quality speech coding with SampleRNN
Janusz Klejsa, Per Hedelin, Cong Zhou +2
We provide a speech coding scheme employing a generative model based on SampleRNN that, while operating at significantly lower bitrates, matches or surpasses the perceptual quality…
Voice Conversion with Conditional SampleRNN
Cong Zhou, Michael Horgan, Vivek Kumar +2
Here we present a novel approach to conditioning the SampleRNN generative model for voice conversion (VC). Conventional methods for VC modify the perceived speaker identity by conv…