Datasets:
language:
- en
license: cc0-1.0
task_categories:
- text-to-audio
- automatic-speech-recognition
- audio-to-audio
- audio-classification
dataset_info:
features:
- name: audio
dtype: audio
- name: speaker_id
dtype: string
- name: transcript
dtype: string
- name: native_language
dtype: string
- name: subset
dtype: string
splits:
- name: all
num_bytes: 3179636720.056
num_examples: 41806
download_size: 3667597693
dataset_size: 3179636720.056
configs:
- config_name: default
data_files:
- split: all
path: data/all-*
ESLTTS
The full paper can be accessed here: arXiv, IEEE Xplore.
Dataset Access
You can access this dataset through Huggingface or Google Driver or IEEE Dataport.
Abstract
With the progress made in speaker-adaptive TTS approaches, advanced approaches have shown a remarkable capacity to reproduce the speaker’s voice in the commonly used TTS datasets. However, mimicking voices characterized by substantial accents, such as non-native English speakers, is still challenging. Regrettably, the absence of a dedicated TTS dataset for speakers with substantial accents inhibits the research and evaluation of speaker-adaptive TTS models under such conditions. To address this gap, we developed a corpus of non-native speakers' English utterances.
We named this corpus “English as a Second Language TTS dataset ” (ESLTTS). The ESLTTS dataset consists of roughly 37 hours of 42,000 utterances from 134 non-native English speakers. These speakers represent a diversity of linguistic backgrounds spanning 31 native languages. For each speaker, the dataset includes an adaptation set lasting about 5 minutes for speaker adaptation, a test set comprising 10 utterances for speaker-adaptive TTS evaluation, and a development set for further research.
Dataset Structure
ESLTTS Dataset/
├─ Malayalam_3/ ------------ {Speaker Native Language}_{Speaker id}
│ ├─ ada_1.flac ------------ {Subset Name}_{Utterance id}
│ ├─ ada_1.txt ------------ Transcription for "ada_1.flac"
│ ├─ test_1.flac ------------ {Subset Name}_{Utterance id}
│ ├─ test_1.txt ------------ Transcription for "test_1.flac"
│ ├─ dev_1.flac ------------ {Subset Name}_{Utterance id}
│ ├─ dev_1.txt ------------ Transcription for "dev_1.flac"
│ ├─ ...
├─ Arabic_3/ ------------ {Speaker Native Language}_{Speaker id}
│ ├─ ada_1.flac ------------ {Subset Name}_{Utterance id}
│ ├─ ...
├─ ...
Citation
@article{wang2024usat,
author = {Wenbin Wang and
Yang Song and
Sanjay K. Jha},
title = {{USAT:} {A} Universal Speaker-Adaptive Text-to-Speech Approach},
journal = {{IEEE} {ACM} Trans. Audio Speech Lang. Process.},
volume = {32},
pages = {2590--2604},
year = {2024},
url = {https://doi.org/10.1109/TASLP.2024.3393714},
doi = {10.1109/TASLP.2024.3393714},
}