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Effective Integration of KAN for Keyword Spotting
Keyword spotting (KWS) is an important speech processing component for smart devices with voice assistance capability.
Query-by-Example Keyword Spotting Using Spectral-Temporal Graph Attentive Pooling and Multi-Task Learning
Existing keyword spotting (KWS) systems primarily rely on predefined keyword phrases.
Disentangled Training with Adversarial Examples For Robust Small-footprint Keyword Spotting
A keyword spotting (KWS) engine that is continuously running on device is exposed to various speech signals that are usually unseen before.
Handling the Alignment for Wake Word Detection: A Comparison Between Alignment-Based, Alignment-Free and Hybrid Approaches
The third, proposed by us, is a hybrid solution in which the model is trained with a small set of aligned data and then tuned with a sizeable unaligned dataset.
LiCo-Net: Linearized Convolution Network for Hardware-efficient Keyword Spotting
This paper proposes a hardware-efficient architecture, Linearized Convolution Network (LiCo-Net) for keyword spotting.
AIPNet: Generative Adversarial Pre-training of Accent-invariant Networks for End-to-end Speech Recognition
As one of the major sources in speech variability, accents have posed a grand challenge to the robustness of speech recognition systems.
