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

Building the Intent Landscape of Real-World Conversational Corpora with Extractive Question-Answering Transformers

no code implementations • 26 Aug 2022 • Jean-Philippe Corbeil, Mia Taige Li, Hadi Abdi Ghavidel

Our pipeline mines intent-span candidates with an extractive Question-Answering Electra model and leverages sentence embeddings to apply a low-level density clustering followed by a top-level hierarchical clustering.

Clustering Extractive Question-Answering +4

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