2 citations · 5 across the 6 of their papers we have counts for
5 papers · 1 filter
XANE Background Acoustic Embeddings: Ablation and Clustering Analysis
Dushyant Sharma, James Fosburgh, Sri Harsha Dumpala +3
We explore the recently proposed explainable acoustic neural embedding~(XANE) system that models the background acoustics of a speech signal in a non-intrusive manner. The XANE emb…
XANE: eXplainable Acoustic Neural Embeddings
Sri Harsha Dumpala, Dushyant Sharma, Chandramouli Shama Sastri +3
We present a novel method for extracting neural embeddings that model the background acoustics of a speech signal. The extracted embeddings are used to estimate specific parameters…
Binaural Speech Enhancement Using Deep Complex Convolutional Transformer Networks
Vikas Tokala, Eric Grinstein, Mike Brookes +3
Studies have shown that in noisy acoustic environments, providing binaural signals to the user of an assistive listening device may improve speech intelligibility and spatial aware…
Uncertainty Quantification in Machine Learning for Joint Speaker Diarization and Identification
Simon W. McKnight, Aidan O. T. Hogg, Vincent W. Neo +1
This paper studies modulation spectrum features () and mel-frequency cepstral coefficients () in joint speaker diarization and identification (JSID). JSID is important as spe…
Subspace Hybrid Beamforming for Head-worn Microphone Arrays
Sina Hafezi, Alastair H. Moore, Pierre Guiraud +4
A two-stage multi-channel speech enhancement method is proposed which consists of a novel adaptive beamformer, Hybrid Minimum Variance Distortionless Response (MVDR), Isotropic-MVD…