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Found 5 papers, 3 papers with code
Speaker Embeddings as Individuality Proxy for Voice Stress Detection
However, the benchmark only evaluates performance separately on each dataset, but does not evaluate performance across the different types of stress and different languages.
Efficient Speech Quality Assessment using Self-supervised Framewise Embeddings
Automatic speech quality assessment is essential for audio researchers, developers, speech and language pathologists, and system quality engineers.
BYOL-S: Learning Self-supervised Speech Representations by Bootstrapping
Our results indicate that the hybrid model with a convolutional transformer as the encoder yields superior performance in most HEAR challenge tasks.
Ranked #1 on
Self-Supervised Learning
on CREMA-D
Hybrid Handcrafted and Learnable Audio Representation for Analysis of Speech Under Cognitive and Physical Load
To that end, we introduce a set of five datasets for task load detection in speech.
SERAB: A multi-lingual benchmark for speech emotion recognition
To facilitate the process, here, we present the Speech Emotion Recognition Adaptation Benchmark (SERAB), a framework for evaluating the performance and generalization capacity of different approaches for utterance-level SER.
