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Causality-Aware CVSS Data Resources
This repository contains generated resources for building causality-aware speech-to-speech translation (S2ST) data from CVSS.
The resources are designed for causality-aware adaptive policy experiments FAST-CAP.
This repository is derived from the CVSS dataset, which is a multilingual-to-English speech-to-speech translation corpus built from Common Voice and CoVoST 2. This repository focuses on the following language directions:
- Spanish → English
- French → English
- German → English
The repository includes examples from the train, dev, and test subsets.
Repository Structure
Causality-Aware-CVSS/
├── raw_sample/
├── generated_resources/
│ ├── a2flow_tts/
│ ├── awesome_align_clean/
│ └── mfa/
│ ├── cvss/
│ └── a2flow_tts/
│ └── cvss/
├── cap_prep_sample/
│ └── cvss_dev_es/
└── README.md
Directory Contents
raw_sample/: Source samples from the Spanish Dev CVSS-T dataset.
generated_resources/: Data resources generated by the causality-aware pipeline:
- a2flow_tts/: Generated target speech with improved speaker similarity and preservation compared to original CVSS-T
- awesome_align_clean/: Text-to-text alignments between source and target languages
- mfa/: Speech-to-text alignments via Montreal Forced Aligner for both original and generated speech
cap_prep_sample/: Causality-aware samples in Lhotse shard format ready for training/validation
Citation
If you use this dataset in your research, please cite the paper below.
@inproceedings{
}
---
license: mit
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