activity
20182026
most citedHigh Fidelity Neural Audio Compression

280 citations · 426 across the 35 of their papers we have counts for

collaborators
Showing cs.CLShow all

18 papers · 1 filter

cs.CL2026

Knowing What to Stress: A Discourse-Conditioned Text-to-Speech Benchmark

Arnon Turetzky, Avihu Dekel, Hagai Aronowitz +2

Spoken meaning often depends not only on what is said, but also on which word is emphasized. The same sentence can convey correction, contrast, or clarification depending on where…

cs.CL2025

ZeroSumEval: An Extensible Framework For Scaling LLM Evaluation with Inter-Model Competition

Hisham A. Alyahya, Haidar Khan, Yazeed Alnumay +2

We introduce ZeroSumEval, a dynamic, competition-based, and evolving evaluation framework for Large Language Models (LLMs) that leverages competitive games. ZeroSumEval encompasses…

cs.CL20253 cited

On The Landscape of Spoken Language Models: A Comprehensive Survey

Siddhant Arora, Kai-Wei Chang, Chung-Ming Chien +7

The field of spoken language processing is undergoing a shift from training custom-built, task-specific models toward using and optimizing spoken language models (SLMs) which act a…

cs.CL2025

Scaling Analysis of Interleaved Speech-Text Language Models

Gallil Maimon, Michael Hassid, Amit Roth +1

Existing Speech Language Model (SLM) scaling analysis paints a bleak picture. It predicts that SLMs require much more compute and data compared to text, leading some to question th…

cs.CL2025

Unsupervised Speech Segmentation: A General Approach Using Speech Language Models

Avishai Elmakies, Omri Abend, Yossi Adi

In this paper, we introduce an unsupervised approach for Speech Segmentation, which builds on previously researched approaches, e.g., Speaker Diarization, while being applicable to…

cs.CL2024

DM-Codec: Distilling Multimodal Representations for Speech Tokenization

Md Mubtasim Ahasan, Md Fahim, Tasnim Mohiuddin +6

Recent advancements in speech-language models have yielded significant improvements in speech tokenization and synthesis. However, effectively mapping the complex, multidimensional…