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Volume 46, Issue 3
  • ISSN 0172-8865
  • E-ISSN: 1569-9730
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Abstract

Recent advances in streaming protocols and automatic speech recognition (ASR) have enabled large-scale spoken language corpora, yet research on Singapore English remains constrained by small or text-based datasets. The YouTube Corpus of Singapore English Podcasts (YCSEP) addresses this gap with 620 hours of transcribed, diarized speech from over 1,300 podcast episodes by Singapore-based content creators. YCSEP supports the empirical analysis of phonetics, morphosyntax, and discourse, enabling the study of low-frequency features like discourse particles and reduplication. The dataset reflects informal, spontaneous speech from diverse speakers and facilitates investigation into nativization and endonormative stabilization processes in postcolonial English. Built using a pipeline of yt-dlp, WhisperX, and Pyannote, YCSEP offers robust empirical grounding for linguistic features such as verb complementation and modality. It also contributes to broader theoretical discussions on areal norms and construction grammar in World Englishes.

© John Benjamins Publishing Company
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2025-09-09
2026-05-16

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The YouTube corpus of Singapore English podcasts
English World-Wide 46, 274 (2025); https://doi.org/10.1075/eww.25018.coa
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  • Article Type: Research Article
Keyword(s): automatic speech recognition; corpus linguistics; discourse particles; grammar; New Englishes; phonetics; Singapore English; whisper

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