Reasoning, a crucial aspect of NLP research, has not been adequately addressed by prevailing models including Large Language Model.
noise terms into the conversation process, thereby constructing a structural causal model (SCM).
Specifically, we design a new network SE-Conformer that can model audio sequences in multiple dimensions and scales, and apply it to the dual-path speech separation framework.
In noisy and reverberant environments, the performance of deep learning-based speech separation methods drops dramatically because previous methods are not designed and optimized for such situations.
Previous database systems extended their SQL dialect to support ML.