jedyang97 / mtag Goto Github PK
View Code? Open in Web Editor NEWCode for NAACL 2021 paper: MTAG: Modal-Temporal Attention Graph for Unaligned Human Multimodal Language Sequences
License: MIT License
Code for NAACL 2021 paper: MTAG: Modal-Temporal Attention Graph for Unaligned Human Multimodal Language Sequences
License: MIT License
杨同学,你好:
我对你的可视化这块的工作非常感兴趣,但是找不到visualizations这个包,能告诉这个包在哪安装的吗?谢谢。
祝科研顺利!
Hi Jed. I am interested in your work MTAG, and I also think it's excellent. I just download the code, prepare the dataset and directly run 'bash run.sh', but I could not get a satisfactory result.
Do you use the same hyperparameters in run.sh to get the numbers reported in the paper? If not, could you please tell me what are the correct hyperparameters to get the best performance? Are there any other details that need to be paid attention to during training?
Thanks.
杨同学你好,我对你的研究比较感兴趣,准备复现你的实验,但是你所提到的实验数据集已经无法在你提供的网址下载了。
请问能否给我提供一下你已经下载的数据集呢?
Hi jed,your job,MTAG,is very excelent. I had some question of it.
I had download the code and run it.I found that the test set in the code may not be used?And perform the measure in the validation after the training step? It is also applied in the past method like Mult?
Hi, I have a confusion about the mosi datasets' preprocessing.
I found two versions of the mosi dataset. For t, a, v, one has dimension with [300,5,20] respectively, rather than another one has dimension with [300,74,47], whatever aligned or unaligned. As far as I know, MOSI audio and vision modality features extracted by COVAREP and Facet have 74 and 47 feature dimensions. So is there a different preprocessing?
Looking forward to hearing from you!
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