32 citations · 38 across the 18 of their papers we have counts for
6 papers · 1 filter
Blind Estimation of Sub-band Acoustic Parameters from Ambisonics Recordings using Spectro-Spatial Covariance Features
Hanyu Meng, Jeroen Breebaart, Jeremy Stoddard +2
Estimating frequency-varying acoustic parameters is essential for enhancing immersive perception in realistic spatial audio creation. In this paper, we propose a unified framework…
A Joint Spectro-Temporal Relational Thinking Based Acoustic Modeling Framework
Zheng Nan, Ting Dang, Vidhyasaharan Sethu +1
Relational thinking refers to the inherent ability of humans to form mental impressions about relations between sensory signals and prior knowledge, and subsequently incorporate th…
AER-LLM: Ambiguity-aware Emotion Recognition Leveraging Large Language Models
Xin Hong, Yuan Gong, Vidhyasaharan Sethu +1
Recent advancements in Large Language Models (LLMs) have demonstrated great success in many Natural Language Processing (NLP) tasks. In addition to their cognitive intelligence, ex…
Dual-Constrained Dynamical Neural ODEs for Ambiguity-aware Continuous Emotion Prediction
Jingyao Wu, Ting Dang, Vidhyasaharan Sethu +1
There has been a significant focus on modelling emotion ambiguity in recent years, with advancements made in representing emotions as distributions to capture ambiguity. However, t…
Binaural Selective Attention Model for Target Speaker Extraction
Hanyu Meng, Qiquan Zhang, Xiangyu Zhang +2
The remarkable ability of humans to selectively focus on a target speaker in cocktail party scenarios is facilitated by binaural audio processing. In this paper, we present a binau…
What is Learnt by the LEArnable Front-end (LEAF)? Adapting Per-Channel Energy Normalisation (PCEN) to Noisy Conditions
Hanyu Meng, Vidhyasaharan Sethu, Eliathamby Ambikairajah
There is increasing interest in the use of the LEArnable Front-end (LEAF) in a variety of speech processing systems. However, there is a dearth of analyses of what is actually lear…