However, there is still a lack of standard in evaluating bias in such machine learning models in the field, which leads to challenges in providing reliable predictions and in addressing disparities.
For example, although combining bio-signals from multiple sensors (i. e., a chest pad sensor and a wrist wearable sensor) has been proved effective for improved performance, wearing multiple devices might be impractical in the free-living context.
A practical approach to improve valence prediction from speech is to adapt the models to the target speakers in the test set.
In this challenge, we open source two large datasets to train AEC models under both single talk and double talk scenarios.
Acoustic echo cancellation Audio and Speech Processing Sound