# An Enhanced Res2Net with Local and Global Feature Fusion for Speaker Verification

arXiv: https://arxiv.org/abs/2305.12838 · HTML: https://mlsanity.com/paper/2305.12838/

## Key facts

- Cited by 42 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 May 2023.

## Built on by (most cited first, 30 of 42)

- [CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language Models](https://mlsanity.com/paper/2412.10117/) (2024)
- [CosyVoice 3: Towards In-the-wild Speech Generation via Scaling-up and Post-training](https://mlsanity.com/paper/2505.17589/) (2025)
- [FunAudioLLM: Voice Understanding and Generation Foundation Models for Natural Interaction Between Humans and LLMs](https://mlsanity.com/paper/2407.04051/) (2024)
- [Step-Audio: Unified Understanding and Generation in Intelligent Speech Interaction](https://mlsanity.com/paper/2502.11946/) (2025)
- [Nes2Net: A Lightweight Nested Architecture for Foundation Model Driven Speech Anti-spoofing](https://mlsanity.com/paper/2504.05657/) (2025)
- [3D-Speaker: A Large-Scale Multi-Device, Multi-Distance, and Multi-Dialect Corpus for Speech Representation Disentanglement](https://mlsanity.com/paper/2306.15354/) (2023)
- [Towards Quantifying and Reducing Language Mismatch Effects in Cross-Lingual Speech Anti-Spoofing](https://mlsanity.com/paper/2409.08346/) (2024)
- [Certification of Speaker Recognition Models to Additive Perturbations](https://mlsanity.com/paper/2404.18791/) (2024)
- [Imperceptible Rhythm Backdoor Attacks: Exploring Rhythm Transformation for Embedding Undetectable Vulnerabilities on Speech Recognition](https://mlsanity.com/paper/2406.10932/) (2024)
- [FlowSE-GRPO: Training Flow Matching Speech Enhancement via Online Reinforcement Learning](https://mlsanity.com/paper/2601.16483/) (2026)
- [FlowTTS-GRPO: Online Reinforcement Learning with Multi-Objective Reward Optimization for Flow-Matching Based Text-to-Speech](https://mlsanity.com/paper/2606.23190/) (2026)
- [The First VoicePrivacy Attacker Challenge](https://mlsanity.com/paper/2504.14183/) (2025)
- [Zero-Shot Voice Conversion via Content-Aware Timbre Ensemble and Conditional Flow Matching](https://mlsanity.com/paper/2411.02026/) (2024)
- [Sparse Autoencoders for Interpretable Emotion Control in Text-to-Speech](https://mlsanity.com/paper/2606.01479/) (2026)
- [Integrating Audio, Visual, and Semantic Information for Enhanced Multimodal Speaker Diarization](https://mlsanity.com/paper/2408.12102/) (2024)
- [MELA-TTS: Joint transformer-diffusion model with representation alignment for speech synthesis](https://mlsanity.com/paper/2509.14784/) (2025)
- [Scores Know Bobs Voice: Speaker Impersonation Attack](https://mlsanity.com/paper/2603.02781/) (2026)
- [X-VC: Zero-shot Streaming Voice Conversion in Codec Space](https://mlsanity.com/paper/2604.12456/) (2026)
- [The First VoicePrivacy Attacker Challenge Evaluation Plan](https://mlsanity.com/paper/2410.07428/) (2024)
- [VoxAging: Continuously Tracking Speaker Aging with a Large-Scale Longitudinal Dataset in English and Mandarin](https://mlsanity.com/paper/2505.21445/) (2025)
- [StarVC: A Unified Auto-Regressive Framework for Joint Text and Speech Generation in Voice Conversion](https://mlsanity.com/paper/2506.02414/) (2025)
- [UtterTune: LoRA-Based Target-Language Pronunciation Edit and Control in Multilingual Text-to-Speech](https://mlsanity.com/paper/2508.09767/) (2025)
- [VoxKnesset: A Large-Scale Longitudinal Hebrew Speech Dataset for Aging Speaker Modeling](https://mlsanity.com/paper/2603.01270/) (2026)
- [ChinaTelecom System Description to VoxCeleb Speaker Recognition Challenge 2023](https://mlsanity.com/paper/2308.08181/) (2023)
- [GMM-ResNext: Combining Generative and Discriminative Models for Speaker Verification](https://mlsanity.com/paper/2407.03135/) (2024)
- [Disentangling Age and Identity with a Mutual Information Minimization Approach for Cross-Age Speaker Verification](https://mlsanity.com/paper/2409.15974/) (2024)
- [MAVFlow: Preserving Paralinguistic Elements with Conditional Flow Matching for Zero-Shot AV2AV Multilingual Translation](https://mlsanity.com/paper/2503.11026/) (2025)
- [A Multi-task Learning Balanced Attention Convolutional Neural Network Model for Few-shot Underwater Acoustic Target Recognition](https://mlsanity.com/paper/2504.13102/) (2025)
- [Seewo's Submission to MLC-SLM: Lessons learned from Speech Reasoning Language Models](https://mlsanity.com/paper/2506.13300/) (2025)
- [LAPS-Diff: A Diffusion-Based Framework for Singing Voice Synthesis With Language Aware Prosody-Style Guided Learning](https://mlsanity.com/paper/2507.04966/) (2025)

## Abstract (arXiv)

Effective fusion of multi-scale features is crucial for improving speaker verification performance. While most existing methods aggregate multi-scale features in a layer-wise manner via simple operations, such as summation or concatenation. This paper proposes a novel architecture called Enhanced Res2Net (ERes2Net), which incorporates both local and global feature fusion techniques to improve the performance. The local feature fusion (LFF) fuses the features within one single residual block to extract the local signal. The global feature fusion (GFF) takes acoustic features of different scales as input to aggregate global signal. To facilitate effective feature fusion in both LFF and GFF, an attentional feature fusion module is employed in the ERes2Net architecture, replacing summation or concatenation operations. A range of experiments conducted on the VoxCeleb datasets demonstrate the superiority of the ERes2Net in speaker verification. Code has been made publicly available at https://github.com/alibaba-damo-academy/3D-Speaker.