A fine-tuned wav2vec2 model trained on the MSP-Podcast corpus for dimensional emotion recognition. It classifies audio into emotional attributes such as arousal, dominance, and valence. Useful for researchers and developers working on affective computing, call center analytics, or human-computer interaction.
Wav2vec2 Large Robust 12 Ft Emotion Msp Dim is a Voice, TTS & speech product. Automatically recognizing emotional dimensions from spoken audio recordings. Wav2vec2 Large Robust 12 Ft Emotion Msp Dim is an open-source project aimed at developers. The project is open source (MIT). Wav2vec2 Large Robust 12 Ft Emotion Msp Dim is available on the web and API.
It is developed by audEERING, and the product first shipped in 2022. The project is developed in the open on GitHub with 555 stars. Among its 3 catalogued features are Emotion Recognition, Audio Classification, and Speech Analysis. It exposes integrations via a public API.
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