arXiv Computation and Language By Maria Teleki, Kimi Wenzel, Anna Seo Gyeong Choi, Tobias Weinberg, Shree Harsha Bokkahalli Satish, Stephanny Sanchez, Belu Ticona, Ariadna Sanchez, Yash Sonkar, Aarti Mathur, Christoph Minixhofer, Abraham Glasser, Raja Kushalnagar, James Caverlee, Minha Lee, Shaomei Wu, Alyssa Hillary Zisk, \'Eva Sz\'ekely, Dylan Gaines, Angelika Seeschaaf Veres, Seray Ibrahim, Nicholas Cummins, Allison Koenecke

A Cross Community Agenda for Speech AI

Read the original on arXiv Computation and Language →

The Flow has not summarised this story yet — read it at arXiv Computation and Language.

arXiv AI
Sep 10

Human or Machine? A Preliminary Turing Test for Speech-to-Speech Interaction

The paper reports the first Turing test for speech‑to‑speech systems, gathering 2,968 human judgments on conversations between nine state‑of‑the‑art S2S systems and 28 humans. None of the evaluated systems passed the test, highlighting a clear gap in human‑likeness. The authors diagnose the failure with an 18‑dimension taxonomy, finding that paralinguistic cues, emotional expressivity, and conversational persona—not semantic understanding—are the main bottlenecks, and they propose an interpretable model for automatic human‑vs‑machine discrimination.

By Xiang Li, Jiabao Gao, Sipei Lin, Xuan Zhou, Chi Zhang, Bo Cheng, Jiale Han, Benyou Wang
arXiv Machine Learning
Jul 28

IndicTalk: A Large-Scale Persona-Based Multilingual Conversational Corpus for Indic Languages

arXiv:2607. 23242v1 Announce Type: cross Abstract: Large Language Models (LLMs) have transformed conversational AI, yet high-quality multilingual code-mixed dialogue resources remain scarce, particularly for Indic languages where speakers naturally alternate between English and their native language in both native-script and Romanized forms.

By Sahil Deepak Gawande, Mayank Singh
arXiv AI
Jul 17

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

arXiv:2607. 14846v1 Announce Type: cross Abstract: 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 systems harness the acoustic information that distinguishes spoken language from its textual representation.

By David Ayllon, Alice Baird, Jeffrey Brooks, Franc Camps-Febrer, Jakub Piotr C{\l}apa, Theo Lebryk, Jens Madsen, Olya Ossipova, Sharath Rao, Hoon Shin, Tigran Soghbatyan, Georg Streich, Rashish Tandon, Panagiotis Tzirakis