5 papers
Location-based Training with Complementary Folded Linear Orderings for Multichannel Speech Separation
Kaixuan Yang, Stijn Kindt, Nilesh Madhu
Location-based training (LBT) effectively resolves the output permutation problem in multichannel speech separation by imposing deterministic spatial orderings. For planar micropho…
Direction of arrival estimation from distant microphone data using single frequency filtering
Sushmita Thakallapalli, Sudarsana Reddy Kadiri, Nilesh Madhu +1
In distant microphones, broadband (BB) methods for direction-of-arrival (DoA) estimation are more suitable than narrowband (NB) methods. Due to the aggregation of their optimizatio…
Single frequency filtering based multi-speaker direction of arrival estimation from stereo recordings
Sushmita Thakallapalli, Sudarsana Reddy Kadiri, Nilesh Madhu +1
Robust direction-of-arrival (DoA) estimation from noisy and reverberant microphone signals remains challenging. Conventional estimators such as generalized cross-correlation (GCC)…
Towards Robust Generative Speech Enhancement Using Vector Quantisation-Based Neural Audio Codec
Haixin Zhao, Nilesh Madhu
This work investigates modelling strategies in continuous and discrete latent spaces in the vector quantisation (VQ)-based neural audio codec (NAC) speech enhancement (SE), along w…
Enhanced Deep Speech Separation in Clustered Ad Hoc Distributed Microphone Environments
Jihyun Kim, Stijn Kindt, Nilesh Madhu +1
Ad-hoc distributed microphone environments, where microphone locations and numbers are unpredictable, present a challenge to traditional deep learning models, which typically requi…