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Papers/Large Raw Emotional Dataset with Aggregation Mechanism

Large Raw Emotional Dataset with Aggregation Mechanism

Vladimir Kondratenko, Artem Sokolov, Nikolay Karpov, Oleg Kutuzov, Nikita Savushkin, Fyodor Minkin

2022-12-23Speech Emotion RecognitionEmotion Recognition
PaperPDFCode(official)

Abstract

We present a new data set for speech emotion recognition (SER) tasks called Dusha. The corpus contains approximately 350 hours of data, more than 300 000 audio recordings with Russian speech and their transcripts. Therefore it is the biggest open bi-modal data collection for SER task nowadays. It is annotated using a crowd-sourcing platform and includes two subsets: acted and real-life. Acted subset has a more balanced class distribution than the unbalanced real-life part consisting of audio podcasts. So the first one is suitable for model pre-training, and the second is elaborated for fine-tuning purposes, model approbation, and validation. This paper describes pre-processing routine, annotation, and experiment with a baseline model to demonstrate some actual metrics which could be obtained with the Dusha data set.

Results

TaskDatasetMetricValueModel
Emotion RecognitionDusha PodcastMacro F10.54Dusha baseline
Emotion RecognitionDusha PodcastUA0.89Dusha baseline
Emotion RecognitionDusha PodcastWA0.53Dusha baseline
Emotion RecognitionDusha CrowdMacro F10.77Dusha baseline
Emotion RecognitionDusha CrowdUA0.83Dusha baseline
Emotion RecognitionDusha CrowdWA0.76Dusha baseline
Speech Emotion RecognitionDusha PodcastMacro F10.54Dusha baseline
Speech Emotion RecognitionDusha PodcastUA0.89Dusha baseline
Speech Emotion RecognitionDusha PodcastWA0.53Dusha baseline
Speech Emotion RecognitionDusha CrowdMacro F10.77Dusha baseline
Speech Emotion RecognitionDusha CrowdUA0.83Dusha baseline
Speech Emotion RecognitionDusha CrowdWA0.76Dusha baseline

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