3 citations · 3 across the 5 of their papers we have counts for
8 papers · 1 filter
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…
Designing Neural Speaker Embeddings with Meta Learning
Manoj Kumar, Tae Jin-Park, Somer Bishop +1
Neural speaker embeddings trained using classification objectives have demonstrated state-of-the-art performance in multiple applications. Typically, such embeddings are trained on…
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…
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…
Meta-learning for robust child-adult classification from speech
Nithin Rao Koluguri, Manoj Kumar, So Hyun Kim +2
Computational modeling of naturalistic conversations in clinical applications has seen growing interest in the past decade. An important use-case involves child-adult interactions…
Learning Domain Invariant Representations for Child-Adult Classification from Speech
Rimita Lahiri, Manoj Kumar, Somer Bishop +1
Diagnostic procedures for ASD (autism spectrum disorder) involve semi-naturalistic interactions between the child and a clinician. Computational methods to analyze these sessions r…