5 accepted papers
Effectively distinguishing the pronunciation correlations between different written texts is a significant issue in linguistic acoustics. Traditionally, such pronunciation correlations are obtained through manually designed pronunciation lexicons. In this paper, we propose a data-driven method to au…
Pseudo-labeling based semi-supervised learning can mitigate the performance degradation resulting from the absence of labeled data in the target domain. In pseudo-labeling, the quality of pseudo-labels is crucial for the final performance. However, most works overlook the potential benefits of using…
In real-world multi-agent systems (MASs), observation delays are ubiquitous, preventing agents from making decisions based on the environment's true state. An individual agent's local observation typically comprises multiple components from other agents or dynamic entities within the environment. Th…
The outbreak of COVID-19 has raised researchers’ attention to audio-based rapid disease detection. Most of the previous studies have obtained competitive detection performance. However, these results are usually obtained by testing data from the same source offline. When making cross-dataset testing…
Despite the recent prevalence of keyword spotting (KWS) in smart-home, open-vocabulary KWS remains a keen but unmet need among the users. In this paper, we propose an RNN Transducer (RNN-T) based keyword spotting system with a constrained attention mechanism biasing module that biases the RNN-T mode…