Leveraging Semantic Information for Efficient Self-Supervised Emotion
Recognition with Audio-Textual Distilled Models

Leveraging Semantic Information for Efficient Self-Supervised Emotion Recognition with Audio-Textual Distilled Models

30 May 2023

Danilo de Oliveira

Papers citing "Leveraging Semantic Information for Efficient Self-Supervised Emotion Recognition with Audio-Textual Distilled Models"

7 / 7 papers shown

Title
Dynamics of Collective Group Affect: Group-level Annotations and the Multimodal Modeling of Convergence and Divergence N. Prabhu Maria Tsfasman Catharine Oertel Timo Gerkmann N. Lehmann-Willenbrock 18 1 0 13 Sep 2024
Improving Personalisation in Valence and Arousal Prediction using Data Augmentation Munachiso Nwadike Jialin Li Hanan Salam 34 0 0 13 Apr 2024
Fusion approaches for emotion recognition from speech using acoustic and text-based features L. Pepino Pablo Riera Luciana Ferrer Agustin Gravano 35 48 0 27 Mar 2024
Distilling HuBERT with LSTMs via Decoupled Knowledge Distillation Danilo de Oliveira Timo Gerkmann VLM 20 3 0 18 Sep 2023
EMOCONV-DIFF: Diffusion-based Speech Emotion Conversion for Non-parallel and In-the-wild Data N. Prabhu Bunlong Lay Simon Welker N. Lehmann-Willenbrock Timo Gerkmann DiffM 14 3 0 14 Sep 2023
In-the-wild Speech Emotion Conversion Using Disentangled Self-Supervised Representations and Neural Vocoder-based Resynthesis N. Prabhu N. Lehmann-Willenbrock Timo Gerkmann 14 3 0 02 Jun 2023
Fine-tuning wav2vec2 for speaker recognition Nik Vaessen David A. van Leeuwen 34 107 0 30 Sep 2021