5 papers · 1 filter
Audio Spotforming via Post-Filtering Using Cross-Array Non-target Estimates
Yuto Ishikawa, Li Li, Shogo Seki +1
Audio spotforming is a technique for extracting target speech from noisy mixtures by utilizing multiple microphone arrays. Conventional methods estimate a shared target speech comp…
Improving DF-Conformer Using Hydra For High-Fidelity Generative Speech Enhancement on Discrete Codec Token
Shogo Seki, Shaoxiang Dang, Li Li
The Dilated FAVOR Conformer (DF-Conformer) is an efficient variant of the Conformer architecture designed for speech enhancement (SE). It employs fast attention through positive or…
Audio Spotforming Using Nonnegative Tensor Factorization with Attractor-Based Regularization
Shoma Ayano, Li Li, Shogo Seki +1
Spotforming is a target-speaker extraction technique that uses multiple microphone arrays. This method applies beamforming (BF) to each microphone array, and the common components…
Improved Remixing Process for Domain Adaptation-Based Speech Enhancement by Mitigating Data Imbalance in Signal-to-Noise Ratio
Li Li, Shogo Seki
RemixIT and Remixed2Remixed are domain adaptation-based speech enhancement (DASE) methods that use a teacher model trained in full supervision to generate pseudo-paired data by rem…
Remixed2Remixed: Domain adaptation for speech enhancement by Noise2Noise learning with Remixing
Li Li, Shogo Seki
This paper proposes Remixed2Remixed, a domain adaptation method for speech enhancement, which adopts Noise2Noise (N2N) learning to adapt models trained on artificially generated (o…