This wav2vec2 based emotion detection model is trained on the [emo-DB dataset](http://emodb.bilderbar.info/start.html).
Code for training can be found [here](https://github.com/padmalcom/wav2vec2-emotion-detection-ger).

Emotion classes are:
  - 0: 'anger'
  - 1: 'boredom'
  - 2: 'disgust'
  - 3: 'fear'
  - 4: 'happiness'
  - 5: 'sadness'
  - 6: 'neutral'

*inference.py* shows, how the model can be used.
{"language": ["de"], "license": "apache-2.0", "tags": ["voice", "classification", "emotion", "speech", "audio"], "datasets": ["emo-DB"], "metrics": ["accuracy"], "widget": [{"src": "https://huggingface.co/padmalcom/wav2vec2-large-emotion-detection-german/resolve/main/test.wav", "example_title": "Sample 1"}], "pipeline_tag": "audio-classification"}
transformers pytorch wav2vec2 voice classification emotion speech audio audio-classification de dataset:emo-DB license:apache-2.0 endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #wav2vec2 #voice #classification #emotion #speech #audio #audio-classification #de #dataset-emo-DB #license-apache-2.0 #endpoints_compatible #has_space #region-us 

This wav2vec2 based emotion detection model is trained on the emo-DB dataset.
Code for training can be found here.

Emotion classes are:
  - 0: 'anger'
  - 1: 'boredom'
  - 2: 'disgust'
  - 3: 'fear'
  - 4: 'happiness'
  - 5: 'sadness'
  - 6: 'neutral'

*URL* shows, how the model can be used.
TAGS
#transformers #pytorch #wav2vec2 #voice #classification #emotion #speech #audio #audio-classification #de #dataset-emo-DB #license-apache-2.0 #endpoints_compatible #has_space #region-us 

TAGS
#transformers #pytorch #wav2vec2 #voice #classification #emotion #speech #audio #audio-classification #de #dataset-emo-DB #license-apache-2.0 #endpoints_compatible #has_space #region-us 
