# GLOBE: A High-quality English Corpus with Global Accents for Zero-shot Speaker Adaptive Text-to-Speech

arXiv: https://arxiv.org/abs/2406.14875 · HTML: https://mlsanity.com/paper/2406.14875/

## Key facts

- Cited by 30 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Jun 2024.

## Built on by (most cited first, 30 of 30)

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- [GE2E-AC: Generalized End-to-End Loss Training for Accent Classification](https://mlsanity.com/paper/2407.14021/) (2024)
- [StyleStream: Real-Time Zero-Shot Voice Style Conversion](https://mlsanity.com/paper/2602.20113/) (2026)
- [PAREDA: A Multi-Accent Speech Dataset of Natural Language Processing Research Discussions](https://mlsanity.com/paper/2605.17860/) (2026)
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- [SPARCLE: SPeaker-aware Aligned Representations via Contrastive Language Embeddings](https://mlsanity.com/paper/2607.01238/) (2026)
- [TokAN: Accent Normalization Using Self-Supervised Speech Tokens](https://mlsanity.com/paper/2607.03928/) (2026)
- [Do Spoken Language Models Hear Speech as They Read Text? Bridging Structural Gaps Between Speech and Text](https://mlsanity.com/paper/2608.22908/) (2026)
- [Context Spanning: A Communication Framework for Full-Duplex Speech Models and External LLM Backends](https://mlsanity.com/paper/2609.33443/) (2026)

## Abstract (arXiv)

This paper introduces GLOBE, a high-quality English corpus with worldwide accents, specifically designed to address the limitations of current zero-shot speaker adaptive Text-to-Speech (TTS) systems that exhibit poor generalizability in adapting to speakers with accents. Compared to commonly used English corpora, such as LibriTTS and VCTK, GLOBE is unique in its inclusion of utterances from 23,519 speakers and covers 164 accents worldwide, along with detailed metadata for these speakers. Compared to its original corpus, i.e., Common Voice, GLOBE significantly improves the quality of the speech data through rigorous filtering and enhancement processes, while also populating all missing speaker metadata. The final curated GLOBE corpus includes 535 hours of speech data at a 24 kHz sampling rate. Our benchmark results indicate that the speaker adaptive TTS model trained on the GLOBE corpus can synthesize speech with better speaker similarity and comparable naturalness than that trained on other popular corpora. We will release GLOBE publicly after acceptance. The GLOBE dataset is available at https://globecorpus.github.io/.