3 accepted papers
While large audio-language models have advanced open-ended audio understanding, they still fall short of nuanced human-level comprehension. This gap persists largely because current benchmarks, limited by data annotations and evaluation metrics, fail to reliably distinguish between generic and highl…
This paper proposes a joint acoustic echo cancellation (AEC) and speech enhancement method with adaptive filter and deep neural network (DNN) model. A partitioned block adaptive filter is adopted for linear AEC followed by a convolutional neural network and transformer based model to suppress the re…
The studies of binaural hearing indicated considerable benefits of the spatial information of sound sources in speech understanding in noise. In this paper, we propose a binaural speech enhancement approach based on deep neural network. In this approach, the signals at the left and right channels ar…