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20162024
most citedTime-Contrastive Learning Based Deep Bottleneck Features for Text-Dependent Speaker Verification

32 citations · 84 across the 27 of their papers we have counts for

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Showing 2018Show all

8 papers · 1 filter

cs.SD2018

Domain Mismatch Robust Acoustic Scene Classification using Channel Information Conversion

Seongkyu Mun, Suwon Shon

In a recent acoustic scene classification (ASC) research field, training and test device channel mismatch have become an issue for the real world implementation. To address the iss…

eess.AS2018

Domain Attentive Fusion for End-to-end Dialect Identification with Unknown Target Domain

Suwon Shon, Ahmed Ali, James Glass

End-to-end deep learning language or dialect identification systems operate on the spectrogram or other acoustic feature and directly generate identification scores for each class.…

cs.CV2018

Noise-tolerant Audio-visual Online Person Verification using an Attention-based Neural Network Fusion

Suwon Shon, Tae-Hyun Oh, James Glass

In this paper, we present a multi-modal online person verification system using both speech and visual signals. Inspired by neuroscientific findings on the association of voice and…

eess.AS2018

Large-scale Speaker Retrieval on Random Speaker Variability Subspace

Suwon Shon, Younggun Lee, Taesu Kim

This paper describes a fast speaker search system to retrieve segments of the same voice identity in the large-scale data. A recent study shows that Locality Sensitive Hashing (LSH…

eess.AS2018

Unsupervised Representation Learning of Speech for Dialect Identification

Suwon Shon, Wei-Ning Hsu, James Glass

In this paper, we explore the use of a factorized hierarchical variational autoencoder (FHVAE) model to learn an unsupervised latent representation for dialect identification (DID)…

eess.AS2018★ 5 cited

Frame-level speaker embeddings for text-independent speaker recognition and analysis of end-to-end model

Suwon Shon, Hao Tang, James Glass

In this paper, we propose a Convolutional Neural Network (CNN) based speaker recognition model for extracting robust speaker embeddings. The embedding can be extracted efficiently…