4.7 Article

Generative emotional AI for speech emotion recognition: The case for synthetic emotional speech augmentation

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Computer Science, Artificial Intelligence

Improving Speech Emotion Recognition With Adversarial Data Augmentation Network

Lu Yi et al.

Summary: This article proposes an adversarial data augmentation network based on generative adversarial networks (GANs) to address the overfitting problem in training deep neural networks with scarce data. The proposed networks generate augmented data rich in emotion information and yield competitive emotion classifiers.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2022)

Proceedings Paper Computer Science, Artificial Intelligence

EMOTION RECOGNITION IN PUBLIC SPEAKING SCENARIOS UTILISING AN LSTM-RNN APPROACH WITH ATTENTION

Alice Baird et al.

Summary: The study discusses the advantages of continuous emotion recognition in public speaking scenarios using speech-based features and biological signal fusion. By training language-independent models and testing them on speeches from various native and non-native speaker groupings, it demonstrates the effectiveness of non-native speakers in emotion recognition tasks.

2021 IEEE SPOKEN LANGUAGE TECHNOLOGY WORKSHOP (SLT) (2021)

Proceedings Paper Computer Science, Artificial Intelligence

Emotions Understanding Model from Spoken Language using Deep Neural Networks and Mel-Frequency Cepstral Coefficients

Marco Giuseppe de Pinto et al.

2020 IEEE INTERNATIONAL CONFERENCE ON EVOLVING AND ADAPTIVE INTELLIGENT SYSTEMS (EAIS) (2020)

Proceedings Paper Computer Science, Information Systems

Federated Learning for Speech Emotion Recognition Applications

Siddique Latif et al.

2020 19TH ACM/IEEE INTERNATIONAL CONFERENCE ON INFORMATION PROCESSING IN SENSOR NETWORKS (IPSN 2020) (2020)

Article Acoustics

Semi-Supervised Speech Emotion Recognition With Ladder Networks

Srinivas Parthasarathy et al.

IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING (2020)

Article Engineering, Electrical & Electronic

An Effective Style Token Weight Control Technique for End-to-End Emotional Speech Synthesis

Ohsung Kwon et al.

IEEE SIGNAL PROCESSING LETTERS (2019)

Article Computer Science, Artificial Intelligence

MSP-IMPROV: An Acted Corpus of Dyadic Interactions to Study Emotion Perception

Carlos Busso et al.

IEEE TRANSACTIONS ON AFFECTIVE COMPUTING (2017)

Article Computer Science, Artificial Intelligence

CREMA-D: Crowd-Sourced Emotional Multimodal Actors Dataset

Houwei Cao et al.

IEEE TRANSACTIONS ON AFFECTIVE COMPUTING (2014)

Review Acoustics

Statistical parametric speech synthesis

Heiga Zen et al.

SPEECH COMMUNICATION (2009)

Article Computer Science, Interdisciplinary Applications

IEMOCAP: interactive emotional dyadic motion capture database

Carlos Busso et al.

LANGUAGE RESOURCES AND EVALUATION (2008)