Paper Reading AI Learner

PCOV-KWS: Multi-task Learning for Personalized Customizable Open Vocabulary Keyword Spotting

2026-03-05 13:57:52
Jianan Pan, Kejie Huang
arXiv_AI
           
Abstract

As advancements in technologies like Internet of Things (IoT), Automatic Speech Recognition (ASR), Speaker Verification (SV), and Text-to-Speech (TTS) lead to increased usage of intelligent voice assistants, the demand for privacy and personalization has escalated. In this paper, we introduce a multi-task learning framework for personalized, customizable open-vocabulary Keyword Spotting (PCOV-KWS). This framework employs a lightweight network to simultaneously perform Keyword Spotting (KWS) and SV to address personalized KWS requirements. We have integrated a training criterion distinct from softmax-based loss, transforming multi-class classification into multiple binary classifications, which eliminates inter-category competition, while an optimization strategy for multi-task loss weighting is employed during training. We evaluated our PCOV-KWS system in multiple datasets, demonstrating that it outperforms the baselines in evaluation results, while also requiring fewer parameters and lower computational resources.

Abstract (translated)

URL

https://arxiv.org/abs/2603.18023

PDF

https://arxiv.org/pdf/2603.18023.pdf

Tags
3D Action Action_Localization Action_Recognition Activity Adversarial Agent Attention Autonomous Bert Boundary_Detection Caption Chat Classification CNN Compressive_Sensing Contour Contrastive_Learning Deep_Learning Denoising Detection Dialog Diffusion Drone Dynamic_Memory_Network Edge_Detection Embedding Embodied Emotion Enhancement Face Face_Detection Face_Recognition Facial_Landmark Few-Shot Gait_Recognition GAN Gaze_Estimation Gesture Gradient_Descent Handwriting Human_Parsing Image_Caption Image_Classification Image_Compression Image_Enhancement Image_Generation Image_Matting Image_Retrieval Inference Inpainting Intelligent_Chip Knowledge Knowledge_Graph Language_Model LLM Matching Medical Memory_Networks Multi_Modal Multi_Task NAS NMT Object_Detection Object_Tracking OCR Ontology Optical_Character Optical_Flow Optimization Person_Re-identification Point_Cloud Portrait_Generation Pose Pose_Estimation Prediction QA Quantitative Quantitative_Finance Quantization Re-identification Recognition Recommendation Reconstruction Regularization Reinforcement_Learning Relation Relation_Extraction Represenation Represenation_Learning Restoration Review RNN Robot Salient Scene_Classification Scene_Generation Scene_Parsing Scene_Text Segmentation Self-Supervised Semantic_Instance_Segmentation Semantic_Segmentation Semi_Global Semi_Supervised Sence_graph Sentiment Sentiment_Classification Sketch SLAM Sparse Speech Speech_Recognition Style_Transfer Summarization Super_Resolution Surveillance Survey Text_Classification Text_Generation Time_Series Tracking Transfer_Learning Transformer Unsupervised Video_Caption Video_Classification Video_Indexing Video_Prediction Video_Retrieval Visual_Relation VQA Weakly_Supervised Zero-Shot