90 citations · 127 across the 8 of their papers we have counts for
10 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…
A Review of Speaker Diarization: Recent Advances with Deep Learning
Tae Jin Park, Naoyuki Kanda, Dimitrios Dimitriadis +3
Speaker diarization is a task to label audio or video recordings with classes that correspond to speaker identity, or in short, a task to identify "who spoke when". In the early ye…
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…
Speaker diarization using latent space clustering in generative adversarial network
Monisankha Pal, Manoj Kumar, Raghuveer Peri +5
In this work, we propose deep latent space clustering for speaker diarization using generative adversarial network (GAN) backprojection with the help of an encoder network. The pro…
Speaker Diarization With Lexical Information
Tae Jin Park, Kyu Han, Ian Lane +1
This work presents a novel approach to leverage lexical information for speaker diarization. We introduce a speaker diarization system that can directly integrate lexical as well a…
Multimodal Speaker Segmentation and Diarization using Lexical and Acoustic Cues via Sequence to Sequence Neural Networks
Tae Jin Park, Panayiotis Georgiou
While there has been substantial amount of work in speaker diarization recently, there are few efforts in jointly employing lexical and acoustic information for speaker segmentatio…