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20192026
most citedMamba in Speech: Towards an Alternative to Self-Attention

6 citations · 17 across the 17 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

eess.AS2024

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…

cs.AI2024

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…

eess.AS2024

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…

eess.AS2024

An Exploration of Length Generalization in Transformer-Based Speech Enhancement

Qiquan Zhang, Hongxu Zhu, Xinyuan Qian +2

The use of Transformer architectures has facilitated remarkable progress in speech enhancement. Training Transformers using substantially long speech utterances is often infeasible…

eess.AS2024★ 6 cited

Mamba in Speech: Towards an Alternative to Self-Attention

Xiangyu Zhang, Qiquan Zhang, Hexin Liu +6

Transformer and its derivatives have achieved success in diverse tasks across computer vision, natural language processing, and speech processing. To reduce the complexity of compu…

eess.AS2024★ 2 cited

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…

eess.AS2024★ 1 cited

An Empirical Study on the Impact of Positional Encoding in Transformer-based Monaural Speech Enhancement

Qiquan Zhang, Meng Ge, Hongxu Zhu +4

Transformer architecture has enabled recent progress in speech enhancement. Since Transformers are position-agostic, positional encoding is the de facto standard component used to…