Speech Technology for Everyone: Automatic Speech Recognition for Non-Native English

no code implementations • ICNLSP 2021 • Toshiko Shibano, Xinyi Zhang, Mia Taige Li, Haejin Cho, Peter Sullivan, Muhammad Abdul-Mageed

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

VoxArabica: A Robust Dialect-Aware Arabic Speech Recognition System

no code implementations • 17 Oct 2023 • Abdul Waheed, Bashar Talafha, Peter Sullivan, AbdelRahim Elmadany, Muhammad Abdul-Mageed

We train a wide range of models such as HuBERT (DID), Whisper, and XLS-R (ASR) in a supervised setting for Arabic DID and ASR tasks.

Arabic Speech Recognition Automatic Speech Recognition +4

On the Robustness of Arabic Speech Dialect Identification

no code implementations • 1 Jun 2023 • Peter Sullivan, AbdelRahim Elmadany, Muhammad Abdul-Mageed

As these pipelines require application of ADI tools to potentially out-of-domain data, we aim to investigate how vulnerable the tools may be to this domain shift.

Dialect Identification Self-Supervised Learning +3

Improving Automatic Speech Recognition for Non-Native English with Transfer Learning and Language Model Decoding

1 code implementation • 10 Feb 2022 • Peter Sullivan, Toshiko Shibano, Muhammad Abdul-Mageed

ASR systems designed for native English (L1) usually underperform on non-native English (L2).

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

Speech Technology for Everyone: Automatic Speech Recognition for Non-Native English with Transfer Learning

no code implementations • 1 Oct 2021 • Toshiko Shibano, Xinyi Zhang, Mia Taige Li, Haejin Cho, Peter Sullivan, Muhammad Abdul-Mageed

To address the performance gap of English ASR models on L2 English speakers, we evaluate fine-tuning of pretrained wav2vec 2. 0 models (Baevski et al., 2020; Xu et al., 2021) on L2-ARCTIC, a non-native English speech corpus (Zhao et al., 2018) under different training settings.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3