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Found 4 papers, 3 papers with code
A Multi-dimensional Deep Structured State Space Approach to Speech Enhancement Using Small-footprint Models
We propose a multi-dimensional structured state space (S4) approach to speech enhancement.
Neural Model Reprogramming with Similarity Based Mapping for Low-Resource Spoken Command Recognition
In this study, we propose a novel adversarial reprogramming (AR) approach for low-resource spoken command recognition (SCR), and build an AR-SCR system.
A Neural State-Space Model Approach to Efficient Speech Separation
In this work, we introduce S4M, a new efficient speech separation framework based on neural state-space models (SSM).
The AS-NU System for the M2VoC Challenge
The first track focuses on using a small number of 100 target utterances for voice cloning, while the second track focuses on using only 5 target utterances for voice cloning.
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