Datasets:
Tasks:
Automatic Speech Recognition
Modalities:
Audio
Formats:
soundfolder
Languages:
English
Size:
< 1K
License:
| license: cc-by-sa-4.0 | |
| task_categories: | |
| - automatic-speech-recognition | |
| language: | |
| - en | |
| [](https://github.com/lottev1991/Project-AIdol-Public-English-Dataset) | |
| [](https://github.com/SilasAntonisen/SynthGT) | |
| [](https://huggingface.co/datasets/Silasimo/SynthGT) | |
| [](https://huggingface.co/collections/Silasimo/synthgt-forced-alignment-experiments) | |
| This dataset contains segmented audio and customized annotations derived from the [Project AI❤dol Public English Dataset](https://github.com/lottev1991/Project-AIdol-Public-English-Dataset) by Lotte V (@lottev1991). The original dataset is licensed under cc-by-sa-4.0, and thus we do the same with this segmented version. To learn more about the terms of use, please refer to the original dataset license. | |
| This dataset has been constructed as a benchmark for singing-oriented forced alignment in our [SynthGT project](https://github.com/SilasAntonisen/SynthGT). | |
| We manually decide on segmentation points in the original Project AI❤dol Public English Dataset to create phrase-level excerpts. We then convert all AP and EP to SP, and manually replace all non-ARPAbet phoneme instances with the best fitting ARBAbet replacement. This was done to make Project AIdol Segmented share the same vocabulary as our [SynthGT dataset](https://huggingface.co/datasets/Silasimo/SynthGT). | |
| We share the audio files in the **wav** folder and the processed versions of the original Project AI❤dol Public English Dataset annotation files in the **processed_annotations** folder. The **lab** folder contains the phoneme sequence of each segment, and the **TextGrid** folder contains the phoneme sequence along with phoneme durations of each segment in TextGrid format. In our experiments we use the **wav** files along with the **lab** folder files to predict phoneme durations, which we compare to the ground truth **TextGrid** files. Our models which we have evaluated with this benchmark are available in our [model collection](https://huggingface.co/collections/Silasimo/synthgt-forced-alignment-experiments). | |
| If you use this dataset for your own experiments or any other purpose, please give proper attribution to the original [Project AI❤dol Public English Dataset](https://github.com/lottev1991/Project-AIdol-Public-English-Dataset) and author Lotte V (@lottev1991), and cite our work: | |
| ``` | |
| bibtex | |
| @unpublished{Antonisen2026SynthGT, | |
| author = {Silas Antonisen and Iván López-Espejo}, | |
| title = {Synthesizing Ground Truth Phoneme Boundaries with SynthGT: A Synthetically Generated Solo-Singing Corpus}, | |
| note = {Submitted to IEEE Transactions on Audio, Speech and Language Processing}, | |
| year = {2026} | |
| } | |
| ``` |