3 citations · 3 across the 5 of their papers we have counts for
7 papers
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…
A study of semi-supervised speaker diarization system using gan mixture model
Monisankha Pal, Manoj Kumar, Raghuveer Peri +1
We propose a new speaker diarization system based on a recently introduced unsupervised clustering technique namely, generative adversarial network mixture model (GANMM). The propo…