论文标题
与空间感知任务的联合多通道语音的BERT
BERT for Joint Multichannel Speech Dereverberation with Spatial-aware Tasks
论文作者
论文摘要
我们提出了一种通过两个空间感知任务的联合多通道语音验证的方法：到达方向（DOA）估计和语音分离。所提出的方法将涉及任务作为序列映射问题的序列解决，这对于各种前端语音增强任务来说已经足够一般。所提出的方法的灵感来自Transformers（BERT）的双向编码器表示的出色序列建模能力。我们没有以自我监督的方式利用明确的表示，而是以监督的方式利用变压器编码的隐藏表示形式。多通道光谱幅度和不同长度话语的光谱相信息均编码。实验结果证明了该方法的有效性。
We propose a method for joint multichannel speech dereverberation with two spatial-aware tasks: direction-of-arrival (DOA) estimation and speech separation. The proposed method addresses involved tasks as a sequence to sequence mapping problem, which is general enough for a variety of front-end speech enhancement tasks. The proposed method is inspired by the excellent sequence modeling capability of bidirectional encoder representation from transformers (BERT). Instead of utilizing explicit representations from pretraining in a self-supervised manner, we utilizes transformer encoded hidden representations in a supervised manner. Both multichannel spectral magnitude and spectral phase information of varying length utterances are encoded. Experimental result demonstrates the effectiveness of the proposed method.
