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Found 6 papers, 1 papers with code
When LLMs Meets Acoustic Landmarks: An Efficient Approach to Integrate Speech into Large Language Models for Depression Detection
In addition, this approach is not only valuable for the detection of depression but also represents a new perspective in enhancing the ability of LLMs to comprehend and process speech signals.
Phonological Level wav2vec2-based Mispronunciation Detection and Diagnosis Method
We further propose a multi-label variant of the Connectionist Temporal Classification (CTC) approach to jointly model the non-mutually exclusive speech attributes using a single model.
Speaker- and Age-Invariant Training for Child Acoustic Modeling Using Adversarial Multi-Task Learning
These high acoustic variations along with the scarcity of child speech corpora have impeded the development of a reliable speech recognition system for children.
The Ambiguous World of Emotion Representation
A key reason for this is the lack of a common mathematical framework to describe all the relevant elements of emotion representations.
Transfer Learning for Improving Speech Emotion Classification Accuracy
The majority of existing speech emotion recognition research focuses on automatic emotion detection using training and testing data from same corpus collected under the same conditions.
Variational Autoencoders for Learning Latent Representations of Speech Emotion: A Preliminary Study
Inspired by this, we propose VAEs for deriving the latent representation of speech signals and use this representation to classify emotions.
