# GLOBE_V3

**Repository Path**: hf-datasets/GLOBE_V3

## Basic Information

- **Project Name**: GLOBE_V3
- **Description**: Mirror of https://huggingface.co/datasets/MushanW/GLOBE_V3
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-08-10
- **Last Updated**: 2025-08-10

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

---
language:
- en
license: cc0-1.0
source_datasets:
- mozilla-foundation/common_voice_14_0
task_categories:
- text-to-audio
- automatic-speech-recognition
- audio-to-audio
- audio-classification
configs:
- config_name: default
  data_files:
  - split: test
    path: data/test-*
  - split: dev
    path: data/dev-*
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: snr
    dtype: float32
  - name: whisper_transcription_large_v3
    dtype: string
  - name: utmos
    dtype: float32
  - name: wer
    dtype: float32
  - name: cer
    dtype: float32
  - name: predicted_gender
    dtype: string
  - name: predicted_accent
    dtype: string
  - name: predicted_age
    dtype: string
  - name: common_voice_path
    dtype: string
  - name: common_voice_sentence_id
    dtype: string
  - name: common_voice_sentence
    dtype: string
  - name: common_voice_age
    dtype: string
  - name: common_voice_gender
    dtype: string
  - name: common_voice_accents
    dtype: string
  - name: audio
    dtype:
      audio:
        sampling_rate: 24000
  splits:
  - name: test
    num_bytes: 2016767055.913
    num_examples: 9179
  - name: dev
    num_bytes: 2212771887.685
    num_examples: 9603
  - name: train
    num_bytes: 180237198132.75
    num_examples: 704750
  download_size: 165538220540
  dataset_size: 184466737076.348
---



# Important notice

Differences between V3 version and two previous versions ([V1](https://huggingface.co/datasets/MushanW/GLOBE_V1)|[V2](https://huggingface.co/datasets/MushanW/GLOBE_V2)):
  
  0.    This version is built base on Common Voice 21.0 English Subset.
  1.	This version only includes utterance that are an exact match with the transcription from Whisper V3 LARGE (CER == 0).
  2.	This version includes the original Common Voice metadata (age, gender, accent, and ID).
  3.	All audio files in this version are at 24kHz sampling rate.
  4.	All audio files in this version are unenhanced. (We’d greatly appreciate it if anyone is willing to provide an API for speech enhancement.)

# Globe

The full paper can be accessed here: [arXiv](https://arxiv.org/abs/2406.14875)

An online demo can be accessed here: [Github](https://globecorpus.github.io/)

## Abstract

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.

## Citation
```
@misc{wang2024globe,
      title={GLOBE: A High-quality English Corpus with Global Accents for Zero-shot Speaker Adaptive Text-to-Speech}, 
      author={Wenbin Wang and Yang Song and Sanjay Jha},
      year={2024},
      eprint={2406.14875},
      archivePrefix={arXiv},
}
```