6 citations · 9 across the 14 of their papers we have counts for
19 papers
Unified Shared Encoder in Spoof-Aware Speaker Verification with Hybrid Wavelet Prompt Tuning
Aref Farhadipour, Srikanth Madikeri, Teodora Vukovic +2
Spoofing-aware speaker verification (SASV) must confirm who is speaking and that the speech is genuine, but current systems gain one at the expense of the other. Modular cascades a…
UZH-CL at ArA-DF 2026: Prompt-Tuned Foundation Models and Track-Adaptive Score Fusion for Arabic Speech Deepfake Detection
Aref Farhadipour, Teodora Vukovic, Petr Motlicek
Detecting synthetic and voice-converted speech remains difficult for low-resource languages with dialectal diversity, where systems must generalize across regional dialects and uns…
Controlling Speaking Rate in Autoregressive TTS via Activation Steering
Francesco Verdini, Antonis Asonitis, Aref Farhadipour +4
Autoregressive text-to-speech (TTS) systems synthesize natural speech but, once trained, offer little control over speaking rate. We show that speaking rate can be steered at infer…
The Limits of Reference-Free Speech Quality Metrics as Evaluators and Rewards on Modern Text-to-Speech
Antonis Asonitis, Juan Pablo Zuluaga Gomez, Francesco Verdini +4
Reference-free quality predictors such as UTMOS, DNSMOS and SCOREQ are the de facto automatic evaluators for text-to-speech (TTS) and are increasingly adopted as reward signals for…
GRAFT: Grafted Reference Audio for Fine-grained Pronunciation in Zero-shot Text-to-Speech
Antonis Asonitis, Francesco Verdini, Aref Farhadipour +4
We present GRAFT, a per-word pronunciation conditioning mechanism for text-to-speech neural codec language modeling. Existing systems reach high intelligibility and naturalness but…
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…
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…
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…
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…
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…
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…
CL-UZH submission to the NIST SRE 2024 Speaker Recognition Evaluation
Aref Farhadipour, Shiran Liu, Masoumeh Chapariniya +4
The CL-UZH team submitted one system each for the fixed and open conditions of the NIST SRE 2024 challenge. For the closed-set condition, results for the audio-only trials were ach…
State-Space Models in Efficient Whispered and Multi-dialect Speech Recognition
Aref Farhadipour, Homayoon Beigi, Volker Dellwo +1
Whispered speech recognition presents significant challenges for conventional automatic speech recognition systems, particularly when combined with dialect variation. However, util…
Quantifying and Reducing Speaker Heterogeneity within the Common Voice Corpus for Phonetic Analysis
Miao Zhang, Aref Farhadipour, Annie Baker +3
With its crosslinguistic and cross-speaker diversity, the Mozilla Common Voice Corpus (CV) has been a valuable resource for multilingual speech technology and holds tremendous pote…
Multimodal Emotion Recognition and Sentiment Analysis in Multi-Party Conversation Contexts
Aref Farhadipour, Hossein Ranjbar, Masoumeh Chapariniya +3
Emotion recognition and sentiment analysis are pivotal tasks in speech and language processing, particularly in real-world scenarios involving multi-party, conversational data. Thi…
Comparative Analysis of Modality Fusion Approaches for Audio-Visual Person Identification and Verification
Aref Farhadipour, Masoumeh Chapariniya, Teodora Vukovic +1
Multimodal learning involves integrating information from various modalities to enhance learning and comprehension. We compare three modality fusion strategies in person identifica…
Leveraging Self-Supervised Models for Automatic Whispered Speech Recognition
Aref Farhadipour, Homa Asadi, Volker Dellwo
In automatic speech recognition, any factor that alters the acoustic properties of speech can pose a challenge to the system's performance. This paper presents a novel approach for…
Facial Emotion Recognition Under Mask Coverage Using a Data Augmentation Technique
Aref Farhadipour, Pouya Taghipour
Identifying human emotions using AI-based computer vision systems, when individuals wear face masks, presents a new challenge in the current Covid-19 pandemic. In this study, we pr…
Gammatonegram Representation for End-to-End Dysarthric Speech Processing Tasks: Speech Recognition, Speaker Identification, and Intelligibility Assessment
Aref Farhadipour, Hadi Veisi
Dysarthria is a disability that causes a disturbance in the human speech system and reduces the quality and intelligibility of a person's speech. Because of this effect, the normal…