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

7 citations · 10 across the 8 of their papers we have counts for

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8 papers

eess.AS20247 cited

Codec-ASR: Training Performant Automatic Speech Recognition Systems with Discrete Speech Representations

Kunal Dhawan, Nithin Rao Koluguri, Ante Jukić +3

Discrete speech representations have garnered recent attention for their efficacy in training transformer-based models for various speech-related tasks such as automatic speech rec…

cs.CL2024

BESTOW: Efficient and Streamable Speech Language Model with the Best of Two Worlds in GPT and T5

Zhehuai Chen, He Huang, Oleksii Hrinchuk +5

Incorporating speech understanding capabilities into pretrained large-language models has become a vital research direction (SpeechLLM). The previous architectures can be categoriz…

cs.CL20241 cited

Less is More: Accurate Speech Recognition & Translation without Web-Scale Data

Krishna C. Puvvada, Piotr Żelasko, He Huang +9

Recent advances in speech recognition and translation rely on hundreds of thousands of hours of Internet speech data. We argue that state-of-the art accuracy can be reached without…

eess.AS2023

The CHiME-7 Challenge: System Description and Performance of NeMo Team's DASR System

Tae Jin Park, He Huang, Ante Jukic +7

We present the NVIDIA NeMo team's multi-channel speech recognition system for the 7th CHiME Challenge Distant Automatic Speech Recognition (DASR) Task, focusing on the development…

eess.AS2023

Property-Aware Multi-Speaker Data Simulation: A Probabilistic Modelling Technique for Synthetic Data Generation

Tae Jin Park, He Huang, Coleman Hooper +5

We introduce a sophisticated multi-speaker speech data simulator, specifically engineered to generate multi-speaker speech recordings. A notable feature of this simulator is its ca…

eess.AS2023

Investigating End-to-End ASR Architectures for Long Form Audio Transcription

Nithin Rao Koluguri, Samuel Kriman, Georgy Zelenfroind +5

This paper presents an overview and evaluation of some of the end-to-end ASR models on long-form audios. We study three categories of Automatic Speech Recognition(ASR) models based…