Context

Speech is the most natural way of expressing ourselves as humans. It is only natural then to extend this communication medium to computer applications. We define speech emotion recognition (SER) systems as a collection of methodologies that process and classify speech signals to detect the embedded emotions. SER is not a new field, it has been around for over two decades, and has regained attention thanks to the recent advancements. These novel studies make use of the advances in all fields of computing and technology, making it necessary to have an update on the current methodologies and techniques that make SER possible. We have identified and discussed distinct areas of SER, provided a detailed survey of current literature of each, and also listed the current challenges.

Content

Here 4 most popular datasets in English: Crema, Ravdess, Savee and Tess. Each of them contains audio in .wav format with some main labels.

Ravdess:

Here is the filename identifiers as per the official RAVDESS website:

  • Modality (01 = full-AV, 02 = video-only, 03 = audio-only).
  • Vocal channel (01 = speech, 02 = song).
  • Emotion (01 = neutral, 02 = calm, 03 = happy, 04 = sad, 05 = angry, 06 = fearful, 07 = disgust, 08 = surprised).
  • Emotional intensity (01 = normal, 02 = strong). NOTE: There is no strong intensity for the 'neutral' emotion.
  • Statement (01 = "Kids are talking by the door", 02 = "Dogs are sitting by the door").
  • Repetition (01 = 1st repetition, 02 = 2nd repetition).
  • Actor (01 to 24. Odd numbered actors are male, even numbered actors are female).

So, here's an example of an audio filename. 02-01-06-01-02-01-12.wav This means the meta data for the audio file is:

  • Video-only (02)
  • Speech (01)
  • Fearful (06)
  • Normal intensity (01)
  • Statement "dogs" (02)
  • 1st Repetition (01)
  • 12th Actor (12) - Female (as the actor ID number is even)

Crema:

The third component is responsible for the emotion label:

  • SAD - sadness;
  • ANG - angry;
  • DIS - disgust;
  • FEA - fear;
  • HAP - happy;
  • NEU - neutral.

Tess:

Very similar to Crema - label of emotion is contained in the name of file.

Savee:

The audio files in this dataset are named in such a way that the prefix letters describes the emotion classes as follows:

  • 'a' = 'anger'
  • 'd' = 'disgust'
  • 'f' = 'fear'
  • 'h' = 'happiness'
  • 'n' = 'neutral'
  • 'sa' = 'sadness'
  • 'su' = 'surprise'

Acknowledgements

My pleasure to show you anotebookof this guy which inspire me to contain this dataset publicly.