4 papers
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…
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…
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…
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…