- Dialogue Datasets: https://www.dropbox.com/s/kojje169drighei/avec_iemocap_meld.zip?dl=0
- Containing AVEC, IEMOCAP and MELD datasets
- Datasets come from https://github.com/SenticNet/conv-emotion
- iemocap_data.pkl, meld_data_original.pkl and AVEC/* are original datasets in the github
- iemocap_data_act.pkl and meld_data_act.pkl are the datasets with dialogue act annotations from https://github.com/bothe/EDAs
- meld_data.pkl is the MELD dataset with dialogue act annotations and pretrained 300d visual features for each utterance
- Set up the configurations in config/run.ini
- python run.py -config config/run.ini
- Dialogue
- mode = run
- pickle_dir_path = /path/to/datasets/. The absolute path of the folder storing the datasets.
- wordvec_path = /path/to/glove_embedding/. The path of the glove embedding file.
- dataset_name in
{'iemocap','meld','avec'}. Name of the dataset. - features in
{'acoustic','visual','textual'}. Multiple modality names should be joined by ','. - label = emotion. Only emotion recognition is supported for the time being.
- dialogue_context in
{'True','False'}. Whether the data is converted to context + current utterance format (the context of a certain length is extracted for each utterance in the dialogue). - context_len. Length of the context. Requires dialogue_context = True.
- seed. The random seed for the experiment.
- load_model_from_dir in
{'True','False'}. Whether the model is loaded from a saved file. - dir_name. The directory storing the model configurations and model parameters. Requires load_model_from_dir = True.
- fine_tune in `{'True','False'}. Whether you want to train the model with the data.
- model specific parameters. For running a model on the dataset, uncomment the respective area of the model and comment the areas for the other models. Please refer to the model implementations in /models/dialogue/ for the meaning of each model specific parameter.
- supported models include but are not limited to:
- BC-LSTM
- CMN
- ICON
- DialogueRNN
- DialogueGCN
- Multimodal-Transformer
- EF-LSTM
- LF-LSTM
- TFN
- MFN
- MARN
- RMFN
- LMF
- Vanilla-LSTHM
- QMN (QMNN)
- Each model is only compatible with dialogue_context = True or dialogue_context = False. For this information, please see the respective block for each model.
- supported models include but are not limited to:
- Set up the configurations in config/grid_search.ini. Tweak a couple of fields in the single run configurations, as instructed below.
- Write up the hyperparameter pool in config/grid_parameters/.
- python run.py -config config/grid_search.ini
- mode = run_grid_search
- grid_parameters_file. The name of file storing the parameters to be searched, under the folder /config/grid_parameters.
- the format of a file is:
- [COMMON]
- var_1 = val_1;val_2;val_3
- var_2 = val_1;val_2;val_3
- the format of a file is:
- search_times. The number of times the program searches in the pool of parameters.
- output_file. The file storing the performances for each search in the pool of parameters. By default, it is eval/grid_search_
{dataset_name}_{network_type}.csv