Baselines and Protocols for Household Speaker Recognition
원문 초록
Speaker recognition on household devices, such as smart speakers, features several challenges: (i) robustness across a vast number of heterogeneous domains (households), (ii) short utterances, (iii) possibly absent speaker labels of the enrollment data (passive enrollment), and (iv) presence of unknown persons (guests). While many commercial products exist, there is less published research and no publicly-available evaluation protocols or open-source baselines. Our work serves to bridge this gap by providing an accessible evaluation benchmark derived from public resources (VoxCeleb and ASVspoof 2019 data) along with a preliminary pool of open-source baselines. This includes four algorithms for active enrollment (speaker labels available) and one algorithm for passive enrollment.
함께 살펴볼 논문
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CoLMbo: Speaker Language Model for Descriptive Profiling
Private kNN-VC: Interpretable Anonymization of Converted Speech
SEED: Speaker Embedding Enhancement Diffusion Model
USEF-TSE: Universal Speaker Embedding Free Target Speaker Extraction
VoxSim: A perceptual voice similarity dataset
Reshape Dimensions Network for Speaker Recognition
토론
이 논문과 연결된 포럼 글이 아직 없습니다.