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From the 1 of 15 linked papers with an AI index.

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20242026
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cs.CL2026

Voice Memory for Agentic Speech Recognition

Chao-Han Huck Yang, Zih-Ching Chen, Piotr Zelasko +3

The paper introduces Voice Memory, an inference-only framework for agentic speech recognition that uses a frozen corrector and a per‑domain memory file to decide when to modify hyp…

cs.CL2026

Preference-ASR: A Preference-Aware Test Set for Benchmarking ASR in the Era of Speech LLMs

Nithin Rao Koluguri, Sasha Meister, Nikolay Karpov +4

Popular ASR test sets adopt inconsistent conventions for numbers, disfluencies, entities, and casing, while standard normalizers erase the format distinctions users care about. Cur…

cs.CL2026

Open ASR Leaderboard: Towards Reproducible and Transparent Multilingual and Long-Form Speech Recognition Evaluation

Vaibhav Srivastav, Steven Zheng, Eric Bezzam +6

We present the Open ASR Leaderboard, a reproducible benchmarking platform with community contributions from academia and industry. It compares 86 open-source and proprietary system…

cs.CL2025

NeKo: Cross-Modality Post-Recognition Error Correction with Tasks-Guided Mixture-of-Experts Language Model

Yen-Ting Lin, Zhehuai Chen, Piotr Zelasko +11

Construction of a general-purpose post-recognition error corrector poses a crucial question: how can we most effectively train a model on a large mixture of domain datasets? The an…

cs.CL2025

Canary-1B-v2 & Parakeet-TDT-0.6B-v3: Efficient and High-Performance Models for Multilingual ASR and AST

Monica Sekoyan, Nithin Rao Koluguri, Nune Tadevosyan +5

This report introduces Canary-1B-v2, a fast, robust multilingual model for Automatic Speech Recognition (ASR) and Speech-to-Text Translation (AST). Built with a FastConformer encod…

cs.CL2025

SALM-Duplex: Efficient and Direct Duplex Modeling for Speech-to-Speech Language Model

Ke Hu, Ehsan Hosseini-Asl, Chen Chen +7

Spoken dialogue is an intuitive form of human-computer interaction, yet current speech language models often remain constrained to turn-based exchanges, lacking real-time adaptabil…