Lost in Transcription: Identifying and Quantifying the Accuracy Biases of Automatic Speech Recognition Systems Against Disfluent Speech

10 May 2024

Papers citing "Lost in Transcription: Identifying and Quantifying the Accuracy Biases of Automatic Speech Recognition Systems Against Disfluent Speech"

3 / 3 papers shown

Title
Assessing ASR Model Quality on Disordered Speech using BERTScore Jimmy Tobin Qisheng Li Subhashini Venugopalan Katie Seaver Richard Cave Katrin Tomanek 29 12 0 21 Sep 2022
SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing Junyi Ao Rui Wang Long Zhou Chengyi Wang Shuo Ren ... Yu Zhang Zhihua Wei Yao Qian Jinyu Li Furu Wei 115 193 0 14 Oct 2021
SEP-28k: A Dataset for Stuttering Event Detection From Podcasts With People Who Stutter Colin S. Lea Vikramjit Mitra A. Joshi S. Kajarekar Jeffrey P. Bigham 40 94 0 24 Feb 2021