most citedThe 6th Affective Behavior Analysis in-the-wild (ABAW) Competition

1 citations · 1 across the 7 of their papers we have counts for

collaborators

7 papers

cs.SD2026

Towards Quantifying Benchmark Optimization in ASR Models

Theo Lebryk, David Ayllon, Alice Baird +3

Public benchmarks are important measures of Automatic Speech Recognition (ASR) model capabilities. However, by nature of being public, there is risk of models being optimized for t…

cs.SD2026

RW-Voice-EQ Bench: A Real World Benchmark for Evaluating Voice AI Systems

David Ayllon, Alice Baird, Jeffrey Brooks +11

Current voice AI benchmarks typically evaluate isolated capabilities such as speech intelligibility, word error rate, or text-based dialogue quality, but they rarely test whether s…

cs.AI2026

The 2026 ACII Dyadic Conversations (DaiKon) Workshop & Challenge

Panagiotis Tzirakis, Alice Baird, Jeffrey Brooks +6

The 2026 ACII Dyadic Conversations (ACII-DaiKon) Workshop & Challenge introduces a benchmark for modeling interpersonal affect and social dynamics in dyadic conversations. Although…

cs.SD2026

TADA: A Generative Framework for Speech Modeling via Text-Acoustic Dual Alignment

Trung Dang, Sharath Rao, Ananya Gupta +6

Modern Text-to-Speech (TTS) systems increasingly leverage Large Language Model (LLM) architectures to achieve scalable, high-fidelity, zero-shot generation. However, these systems…

eess.AS2024

DB3V: A Dialect Dominated Dataset of Bird Vocalisation for Cross-corpus Bird Species Recognition

Xin Jing, Luyang Zhang, Jiangjian Xie +3

In ornithology, bird species are known to have variedit's widely acknowledged that bird species display diverse dialects in their calls across different regions. Consequently, comp…

cs.SD2024

The NeurIPS 2023 Machine Learning for Audio Workshop: Affective Audio Benchmarks and Novel Data

Alice Baird, Rachel Manzelli, Panagiotis Tzirakis +7

The NeurIPS 2023 Machine Learning for Audio Workshop brings together machine learning (ML) experts from various audio domains. There are several valuable audio-driven ML tasks, fro…

cs.CV2024★ 1 cited

The 6th Affective Behavior Analysis in-the-wild (ABAW) Competition

Dimitrios Kollias, Panagiotis Tzirakis, Alan Cowen +6

This paper describes the 6th Affective Behavior Analysis in-the-wild (ABAW) Competition, which is part of the respective Workshop held in conjunction with IEEE CVPR 2024. The 6th A…