IEMOCAP datasets question

[yuanjiechen]

Thank you for sharing your work ! I'm confused about the data read from dataset IEMOCAP.pkl

` iemocap_data = pickle.load(open(data_path + "iemocap.pkl", 'rb'), encoding='bytes') print(np.sum(iemocap_data[b'happy'][TRAIN][TEXT]))

print("------------------------------------")

print(np.sum(iemocap_data[b'sad'][TRAIN][TEXT]))

print("------------------------------------")

print(np.sum(iemocap_data[b'angry'][TRAIN][TEXT]))

print("------------------------------------")

print(np.sum(iemocap_data[b'neutral'][TRAIN][TEXT]))

` I use the above "print" to show the vector value in four classes, but I get the same result like the following:

` Temp location for models: models/model__b'angry'.pt Grid search results are in: results/results__b'angry'.csv -7770.0356465404475

-7770.0356465404475

-7770.0356465404475

-7770.0356465404475 Audio feature dimension is: 74 Visual feature dimension is: 35 Text feature dimension is: 300 `

Meanwhile, I try another keys "VIDEO" and "AUDIO", the four classes value are still same. No matter how I choose the emotion value, the dataset is the same.

The reason I find this is that I want to know how many data in each emotion type, but I get the same length of "train_set" when I switch the parameter "emotion".

And may I ask why don't you train with all emotions together

Thanks