Transformers have rapidly become the preferred choice for audio classification, surpassing methods based on CNNs. However, Audio Spectrogram Transformers (ASTs) exhibit quadratic scaling due to self-attention. The removal of this quadratic self-attention cost presents an appealing direction. Recently, state space models (SSMs), such as Mamba, have demonstrated potential in language and vision tasks in this regard. In this study, we explore whether reliance on self-attention is necessary for audio classification tasks. By introducing Audio Mamba (AuM), the first self-attention-free, purely SSM-based model for audio classification, we aim to address this question. We evaluate AuM on various audio datasets - comprising six different benchmarks - where it achieves comparable or better performance compared to well-established AST model.
An overview of neural architectures for self-supervised audio representation learning from masked spectrograms
Department of Electronic Systems, Aalborg University（电子系统系，奥尔堡大学）；Pioneer Centre for Artificial Intelligence（人工智能先锋中心）；National and Kapodistrian University of Athens（雅典国家与卡波蒂斯坦大学）
An Analysis of Untrained Deep Reservoir Networks for Audio Surveillance
Department of Computer Science University of Pisa Pisa, Italy (ORCID: 0009-0002-6500-9578)；Department of Computer Science University of Pisa Pisa, Italy (ORCID: 0000-0001-8504-1503)
HELIX: Scaling Raw Audio Understanding with Hybrid Mamba-Attention Beyond the Quadratic Limit
Department of Computer Science, University of Freiburg, Freiburg im Breisgau, Germany（弗赖堡大学计算机科学系，德国弗赖堡市）；Department of Computer Engineering（计算机工程系）；Information Technology, Veermata Jijabai Technological Institute, Mumbai, India（维尔玛塔·吉贾拜技术学院信息科技系，印度孟买）
TRAMBA: A Hybrid Transformer and Mamba Architecture for Practical Audio and Bone Conduction Speech Super Resolution and Enhancement on Mobile and Wearable Platforms
RawBMamba: End-to-End Bidirectional State Space Model for Audio Deepfake Detection
School of Computer Science and Technology, Anhui University（安徽大学计算机科学与技术学院）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；Tsinghua University（清华大学）
Mamba in Speech: Towards an Alternative to Self-Attention
School of Electrical Engineering and Telecommunications, The University of New South Wales (UNSW)（新南威尔士大学电子工程与电信学院）；College of Computing and Data Science, Nanyang Technological University（南洋理工大学计算机与数据科学学院）；School of Computer and Communication Engineering, University of Science and Technology Beijing（北京科技大学计算机与通信工程学院）；Guangdong Provincial Key Laboratory of Big Data Computing, The Chinese University of Hong Kong (Shenzhen)（广东大数据计算省级重点实验室，香港中文大学（深圳））；Shenzhen Research Institute of Big data, Shenzhen（深圳大数据研究 institute）
CleanUMamba: A Compact Mamba Network for Speech Denoising using Channel Pruning
Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology（电气工程、数学和计算机科学学院，代尔夫特理工大学）；Leiden Institute of Advanced Computer Science (LIACS), Leiden University（先进计算机科学研究所（LIACS），莱顿大学）
ASCMamba: Multimodal Time-Frequency Mamba for Acoustic Scene Classification
School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, China（海洋科学与技术学院，西北工业大学，西安，中国）；School of Automation, Northwestern Polytechnical University, Xi’an, China（自动化学院，西北工业大学，西安，中国）；School of Electrical Engineering, KAIST, Daejeon, Republic of Korea（电气工程学院，韩国成均馆大学，大田，韩国）
PARROT: Synergizing Mamba and Attention-based SSL Pre-Trained Models via Parallel Branch Hadamard Optimal Transport for Speech Emotion Recognition
IIIT-DelhiIndia（印度IIIT-德尔hi大学）；V.B.S.P.UIndia（印度V.B.S.P.U大学）；UPESIndia（印度UPES大学）；Independent ResearcherIndia（印度独立研究者）；University of TartuEstonia（爱沙尼亚塔尔图大学）；Plaksha UniversityIndia（印度Plaksha大学）
Cross-attention Inspired Selective State Space Models for Target Sound Extraction
National Key Laboratory of General Artificial Intelligence（国家级通用人工智能重点实验室）；School of Intelligence Science and Technology（智能科学与技术学院）；Peking University（北京大学）
Bangla Music Genre Classification Using Bidirectional LSTMS
Dept. of Computer Science \& Engineering, Bangladesh Army International University of Science；Technology, Cumilla Cantonment, Cumilla - 3501, Bangladesh Dept. of Computer Science \& Engineering, CCN University of Science；Technology, CCN Road, Cumilla - 3506, Bangladesh. Dept. of Electrical \& Electronic Engineering, International Islamic University Chittagong,Chattogram - 4318, Bangladesh.
