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20192026
most citedCodec-ASR: Training Performant Automatic Speech Recognition Systems with Discrete Speech Representations

7 citations · 16 across the 20 of their papers we have counts for

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cs.CL2026

Enabling Streaming User Transcription in Full-Duplex Speech-to-Speech Models

Ke Hu, Nourchene Ferchichi, Edresson Casanova +9

Full-duplex speech-to-speech (S2S) models enable natural conversational AI by allowing simultaneous listening and speaking. However, these models typically lack inherent user speec…

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.CL2025

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

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

Granary: Speech Recognition and Translation Dataset in 25 European Languages

Nithin Rao Koluguri, Monica Sekoyan, George Zelenfroynd +12

Multi-task and multilingual approaches benefit large models, yet speech processing for low-resource languages remains underexplored due to data scarcity. To address this, we presen…

cs.CL20251 cited

Training and Inference Efficiency of Encoder-Decoder Speech Models

Piotr Żelasko, Kunal Dhawan, Daniel Galvez +7

Attention encoder-decoder model architecture is the backbone of several recent top performing foundation speech models: Whisper, Seamless, OWSM, and Canary-1B. However, the reporte…