most citedImproved Decoding of Attentional Selection in Multi-Talker Environments with Self-Supervised Learned Speech Representation

1 citations · 1 across the 3 of their papers we have counts for

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eess.AS2023

SLMGAN: Exploiting Speech Language Model Representations for Unsupervised Zero-Shot Voice Conversion in GANs

Yinghao Aaron Li, Cong Han, Nima Mesgarani

In recent years, large-scale pre-trained speech language models (SLMs) have demonstrated remarkable advancements in various generative speech modeling applications, such as text-to…

eess.AS2023

Online Binaural Speech Separation of Moving Speakers With a Wavesplit Network

Cong Han, Nima Mesgarani

Binaural speech separation in real-world scenarios often involves moving speakers. Most current speech separation methods use utterance-level permutation invariant training (u-PIT)…

eess.AS2023★ 1 cited

Improved Decoding of Attentional Selection in Multi-Talker Environments with Self-Supervised Learned Speech Representation

Cong Han, Vishal Choudhari, Yinghao Aaron Li +1

Auditory attention decoding (AAD) is a technique used to identify and amplify the talker that a listener is focused on in a noisy environment. This is done by comparing the listene…