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Found 5 papers, 2 papers with code
HyperVQ: MLR-based Vector Quantization in Hyperbolic Space
However, since the VQVAE is trained with a reconstruction objective, there is no constraint for the embeddings to be well disentangled, a crucial aspect for using them in discriminative tasks.
Advancing Large Multi-modal Models with Explicit Chain-of-Reasoning and Visual Question Generation
The increasing demand for intelligent systems capable of interpreting and reasoning about visual content requires the development of Large Multi-Modal Models (LMMs) that are not only accurate but also have explicit reasoning capabilities.
The Sound Demixing Challenge 2023 $\unicode{x2013}$ Music Demixing Track
We propose a formalization of the errors that can occur in the design of a training dataset for MSS systems and introduce two new datasets that simulate such errors: SDXDB23_LabelNoise and SDXDB23_Bleeding.
SATTS: Speaker Attractor Text to Speech, Learning to Speak by Learning to Separate
The mapping of text to speech (TTS) is non-deterministic, letters may be pronounced differently based on context, or phonemes can vary depending on various physiological and stylistic factors like gender, age, accent, emotions, etc.
MMDenseLSTM: An efficient combination of convolutional and recurrent neural networks for audio source separation
Deep neural networks have become an indispensable technique for audio source separation (ASS).
Ranked #17 on
Music Source Separation
on MUSDB18
(using extra training data)
Music Source Separation
Sound
Audio and Speech Processing
