Textless (ASR-transcript free) Spoken Question Answering. The official release of NMSQA dataset and the implementation of "DUAL: Textless Spoken Question Answering with Speech Discrete Unit Adaptive Learning" paper.
License: Creative Commons Attribution Share Alike 4.0 International
I'm recently doing some experiments on NMSQA, and the code for DUAL provided here are really helpful! While I encountered some difficulty building the units using scripts provided to reproduce the results. Particularly, I'm trying to extract the units for each segment of context, while the preprocessed ones currently provided in the repo are already concatenated for each article following the standard QA scheme (using the merge_passage.py, I guess). May I know if the preprocessed units for each segment could be provided?
Thank you!
P.S. Just seen you and had some chat on Interspeech at the poster. The work was really impressive and useful for us :)
Brilliant works! We are trying to train this model and we find that only codes of contexts are provided in the processed data link. Would you mind providing the processed codes of questions of train and dev split? since the preprocess pipeline is a little time consuming.