28 citations · 36 across the 5 of their papers we have counts for
9 papers
Tackling Dynamics in Federated Incremental Learning with Variational Embedding Rehearsal
Tae Jin Park, Kenichi Kumatani, Dimitrios Dimitriadis
Federated Learning is a fast growing area of ML where the training datasets are extremely distributed, all while dynamically changing over time. Models need to be trained on client…
Multi-Scale Speaker Diarization With Neural Affinity Score Fusion
Tae Jin Park, Manoj Kumar, Shrikanth Narayanan
Identifying the identity of the speaker of short segments in human dialogue has been considered one of the most challenging problems in speech signal processing. Speaker representa…
Meta-learning with Latent Space Clustering in Generative Adversarial Network for Speaker Diarization
Monisankha Pal, Manoj Kumar, Raghuveer Peri +5
The performance of most speaker diarization systems with x-vector embeddings is both vulnerable to noisy environments and lacks domain robustness. Earlier work on speaker diarizati…
Speaker Diarization with Lexical Information
Tae Jin Park, Kyu J. Han, Jing Huang +4
This work presents a novel approach for speaker diarization to leverage lexical information provided by automatic speech recognition. We propose a speaker diarization system that c…
Auto-Tuning Spectral Clustering for Speaker Diarization Using Normalized Maximum Eigengap
Tae Jin Park, Kyu J. Han, Manoj Kumar +1
In this study, we propose a new spectral clustering framework that can auto-tune the parameters of the clustering algorithm in the context of speaker diarization. The proposed fram…
Automatic prediction of suicidal risk in military couples using multimodal interaction cues from couples conversations
Sandeep Nallan Chakravarthula, Md Nasir, Shao-Yen Tseng +6
Suicide is a major societal challenge globally, with a wide range of risk factors, from individual health, psychological and behavioral elements to socio-economic aspects. Military…