/emodet

Implement state-of-the-art models for emotion detection in conversation.

Primary LanguagePython

emodet

Implement state-of-the-art models for emotion detection in conversation.

Datasets

For the original IEMOCAP dataset, utterances are annotated with categorical labels, which are among angry, disgust, fear, frustrated, sad, neutral, excited, happy, surprised, other and XXX (when annotators were not able to have agreement on the label). For example, if we only retain utterances with emotions of angry, frustrated, sad, neutral, excited, happy, just like what some works on emotion detection such as DialogueRNN does, the statistics of each session(s1-s5) are as follows:

session id # utterances
s1 1365
s2 1348
s3 1533
s4 1512
s5 1622

Previous works modified some XXXs to meanningful labels for the need of a better research. However, they don't provide details for this modification. Hence, I conducted a reverse analysis on some given features data and found out following XXX labels are all changed to "hap":

session id utterance id
s1 Ses01F_impro03_F007, Ses01F_impro03_F011, Ses01F_impro03_F014, Ses01F_impro03_M012, Ses01F_impro06_M017, Ses01F_impro07_F007, Ses01M_impro03_F000, Ses01M_impro07_F002
s2 Ses02F_impro03_F002, Ses02F_impro03_F005, Ses02F_impro03_F006, Ses02F_impro03_F007, Ses02F_impro03_F020, Ses02M_impro03_F010, Ses02M_impro03_F026, Ses02M_impro03_F027
s3 Ses03F_impro02_M003, Ses03F_impro03_F000, Ses03F_impro03_F003, Ses03F_impro03_F010, Ses03F_impro03_M003, Ses03F_impro03_M008, Ses03F_impro03_M013, Ses03F_impro03_M016, Ses03F_impro03_M019, Ses03F_impro04_M020, Ses03F_impro07_F000, Ses03F_impro07_F002, Ses03F_impro07_F006, Ses03F_impro07_M016, Ses03F_impro07_M020, Ses03F_impro07_M031, Ses03M_impro02_F001, Ses03M_impro03_F000, Ses03M_impro03_F019, Ses03M_impro03_M005, Ses03M_impro03_M006, Ses03M_impro03_M008, Ses03M_impro03_M009, Ses03M_impro03_M010, Ses03M_impro03_M024, Ses03M_impro03_M025, Ses03M_impro03_M026, Ses03M_impro03_M027, Ses03M_impro03_M034, Ses03M_impro03_M036, Ses03M_impro03_M037, Ses03M_impro05a_F017, Ses03M_impro07_F020, Ses03M_impro07_M001, Ses03M_impro07_M012, Ses03M_impro07_M021
s5 Ses05F_impro07_M010

These changes lead to a new statistics which is the same with that DialogueRNN reported:

session id # utterances
s1 1373
s2 1356
s3 1569
s4 1512
s5 1623