activity
20242026
most citedComparative Analysis of Modality Fusion Approaches for Audio-Visual Person Identification and Verification

2 citations · 2 across the 9 of their papers we have counts for

collaborators

11 papers

cs.CV2026

Foundation Model Embeddings Meet Blended Emotions: A Multimodal Fusion Approach for the BLEMORE Challenge

Masoumeh Chapariniya, Aref Farhadipour, Sarah Ebling +2

We present our system for the BLEMORE Challenge at FG 2026 on blended emotion recognition with relative salience prediction. Our approach combines six encoder families through late…

eess.AS2026

TidyVoice 2026 Challenge Evaluation Plan

Aref Farhadipour, Jan Marquenie, Srikanth Madikeri +6

The performance of speaker verification systems degrades significantly under language mismatch, a critical challenge exacerbated by the field's reliance on English-centric data. To…

cs.CV2026

Adaptive Multimodal Person Recognition: A Robust Framework for Handling Missing Modalities

Aref Farhadipour, Teodora Vukovic, Volker Dellwo +2

Person identification systems often rely on audio, visual, or behavioral cues, but real-world conditions frequently present with missing or degraded modalities. To address this cha…

eess.AS2026

Spoofing-Aware Speaker Verification via Wavelet Prompt Tuning and Multi-Model Ensembles

Aref Farhadipour, Ming Jin, Valeriia Vyshnevetska +3

This paper describes the UZH-CL system submitted to the SASV section of the WildSpoof 2026 challenge. The challenge focuses on the integrated defense against generative spoofing at…

eess.AS2026

TidyVoice: A Curated Multilingual Dataset for Speaker Verification Derived from Common Voice

Aref Farhadipour, Jan Marquenie, Srikanth Madikeri +1

The development of robust, multilingual speaker recognition systems is hindered by a lack of large-scale, publicly available and multilingual datasets, particularly for the read-sp…

eess.AS2025

Towards Language-Independent Face-Voice Association with Multimodal Foundation Models

Aref Farhadipour, Teodora Vukovic, Volker Dellwo

This paper describes the UZH-CL system submitted to the FAME2026 Challenge. The challenge focuses on cross-modal verification under unique multilingual conditions, specifically uns…