most citedReducing Barriers to Self-Supervised Learning: HuBERT Pre-training with Academic Compute

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cs.CL2024

CMU's IWSLT 2024 Simultaneous Speech Translation System

Xi Xu, Siqi Ouyang, Brian Yan +5

This paper describes CMU's submission to the IWSLT 2024 Simultaneous Speech Translation (SST) task for translating English speech to German text in a streaming manner. Our end-to-e…

cs.CL2024

Towards Robust Speech Representation Learning for Thousands of Languages

William Chen, Wangyou Zhang, Yifan Peng +7

Self-supervised learning (SSL) has helped extend speech technologies to more languages by reducing the need for labeled data. However, models are still far from supporting the worl…

cs.CL2024

On the Evaluation of Speech Foundation Models for Spoken Language Understanding

Siddhant Arora, Ankita Pasad, Chung-Ming Chien +9

The Spoken Language Understanding Evaluation (SLUE) suite of benchmark tasks was recently introduced to address the need for open resources and benchmarking of complex spoken langu…

cs.CL2024

On the Effects of Heterogeneous Data Sources on Speech-to-Text Foundation Models

Jinchuan Tian, Yifan Peng, William Chen +3

The Open Whisper-style Speech Model (OWSM) series was introduced to achieve full transparency in building advanced speech-to-text (S2T) foundation models. To this end, OWSM models…

cs.CL2023

Reproducing Whisper-Style Training Using an Open-Source Toolkit and Publicly Available Data

Yifan Peng, Jinchuan Tian, Brian Yan +13

Pre-training speech models on large volumes of data has achieved remarkable success. OpenAI Whisper is a multilingual multitask model trained on 680k hours of supervised speech dat…

cs.CL2023

Joint Prediction and Denoising for Large-scale Multilingual Self-supervised Learning

William Chen, Jiatong Shi, Brian Yan +6

Multilingual self-supervised learning (SSL) has often lagged behind state-of-the-art (SOTA) methods due to the expenses and complexity required to handle many languages. This furth…