CISPA
Browse
tacl_a_00627.pdf (481.22 kB)

AfriSpeech-200: Pan-African Accented Speech Dataset for Clinical and General Domain ASR

Download (481.22 kB)
journal contribution
posted on 2024-05-24, 07:53 authored by Tobi Olatunji, Tejumade AfonjaTejumade Afonja, Aditya Yadavalli, Chris Chinenye Emezue, Sahib Singh, Bonaventure FP Dossou, Joanne Osuchukwu, Salomey Osei, Atnafu Lambebo Tonja, Naome Etori, Clinton Mbataku
Africa has a very poor doctor-to-patient ratio. At very busy clinics, doctors could see 30+ patients per day—a heavy patient burden compared with developed countries—but productivity tools such as clinical automatic speech recognition (ASR) are lacking for these overworked clinicians. However, clinical ASR is mature, even ubiquitous, in developed nations, and clinician-reported performance of commercial clinical ASR systems is generally satisfactory. Furthermore, the recent performance of general domain ASR is approaching human accuracy. However, several gaps exist. Several publications have highlighted racial bias with speech-to-text algorithms and performance on minority accents lags significantly. To our knowledge, there is no publicly available research or benchmark on accented African clinical ASR, and speech data is non-existent for the majority of African accents. We release AfriSpeech, 200hrs of Pan-African English speech, 67,577 clips from 2,463 unique speakers across 120 indigenous accents from 13 countries for clinical and general domain ASR, a benchmark test set, with publicly available pre-trained models with SOTA performance on the AfriSpeech benchmark.

History

Primary Research Area

  • Trustworthy Information Processing

Journal

Transactions of the Association for Computational Linguistics

Volume

11

Page Range

1669-1685

Publisher

The MIT Press

Open Access Type

  • Gold

Sub Type

  • Article

BibTeX

@article{Olatunji:Afonja:Yadavalli:Emezue:Singh:Dossou:Osuchukwu:Osei:Tonja:Etori:Mbataku:2023, title = "AfriSpeech-200: Pan-African Accented Speech Dataset for Clinical and General Domain ASR", author = "Olatunji, Tobi" AND "Afonja, Tejumade" AND "Yadavalli, Aditya" AND "Emezue, Chris Chinenye" AND "Singh, Sahib" AND "Dossou, Bonaventure FP" AND "Osuchukwu, Joanne" AND "Osei, Salomey" AND "Tonja, Atnafu Lambebo" AND "Etori, Naome" AND "Mbataku, Clinton", year = 2023, month = 12, journal = "Transactions of the Association for Computational Linguistics", pages = "1669--1685", publisher = "The MIT Press", issn = "2307-387X", doi = "10.1162/tacl_a_00627" }