Afrispeech-Dialog: A Benchmark Dataset for Spontaneous English Conversations in Healthcare and Beyond
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Abstract (arXiv)
Speech technologies are transforming interactions across various sectors, from healthcare to call centers and robots, yet their performance on African-accented conversations remains underexplored. We introduce Afrispeech-Dialog, a benchmark dataset of 50 simulated medical and non-medical African-accented English conversations, designed to evaluate automatic speech recognition (ASR) and related technologies. We assess state-of-the-art (SOTA) speaker diarization and ASR systems on long-form, accented speech, comparing their performance with native accents and discover a 10%+ performance degradation. Additionally, we explore medical conversation summarization capabilities of large language models (LLMs) to demonstrate the impact of ASR errors on downstream medical summaries, providing insights into the challenges and opportunities for speech technologies in the Global South. Our work highlights the need for more inclusive datasets to advance conversational AI in low-resource settings.
Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 37 of its 70 references that are in the map. First posted on arXiv 6 Feb 2025.
Builds on
37 of 70 references.
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Citing papers per year: 2025: 3; 2026: 8.
11 papers.
- 2026UbuntuGuard: A Culturally-Grounded Policy Benchmark for Equitable AI Safety in African Languagescited by 5
- 2026The Persona Paradox: Medical Personas as Behavioral Priors in Clinical Language Modelscited by 3
- 2025Domain-Aware Speaker Diarization On African-Accented Englishcited by 2
- 2025Automatic Speech Recognition (ASR) for African Low-Resource Languages: A Systematic Literature Reviewcited by 2
- 2025Can large audio language models understand child stuttering speech? speech summarization, and source separationcited by 2
- 2026Afrispeech Semantics: Evaluating Audio Semantic Reasoning in Spoken Language Models Across Domains and Accentscited by 2
- 2026Reasoning Beyond Transcription: Audio Language Models on Child Stuttering Speechcited by 1
- 2026AfriVox-v2: A Domain-Verticalized Benchmark for In-the-Wild African Speech Recognitioncited by 0
- 2026Beyond Word Error Rate: A Switch Aware Evaluation of ASR and Audio Language Models on English Yoruba Code-Switched Speechcited by 0
- 2026Neyshekar: An Open Persian Read-Speech Corpus for Automatic Speech Recognitioncited by 0
- 2026How Robust Are Neural Audio Codecs for African Speech? A Multi-Task Benchmark and the Limits of Perceptual Qualitycited by 0
- 2026Neyshekar: An Open Persian Read-Speech Corpus for Automatic Speech Recognition13 Sep 2026
- 2026How Robust Are Neural Audio Codecs for African Speech? A Multi-Task Benchmark and the Limits of Perceptual Quality10 Sep 2026
- 2026Beyond Word Error Rate: A Switch Aware Evaluation of ASR and Audio Language Models on English Yoruba Code-Switched Speech10 Sep 2026
- 2026Reasoning Beyond Transcription: Audio Language Models on Child Stuttering Speech7 Sep 2026
- 2026Afrispeech Semantics: Evaluating Audio Semantic Reasoning in Spoken Language Models Across Domains and Accents11 May 2026
- 2026AfriVox-v2: A Domain-Verticalized Benchmark for In-the-Wild African Speech Recognition5 May 2026
- 2026UbuntuGuard: A Culturally-Grounded Policy Benchmark for Equitable AI Safety in African Languages19 Jan 2026
- 2026The Persona Paradox: Medical Personas as Behavioral Priors in Clinical Language Models8 Jan 2026
- 2025Can large audio language models understand child stuttering speech? speech summarization, and source separation21 Oct 2025
- 2025Automatic Speech Recognition (ASR) for African Low-Resource Languages: A Systematic Literature Review1 Oct 2025
- 2025Domain-Aware Speaker Diarization On African-Accented English25 Sep 2025