← Search

Nauman Dawalatabad

3 accepted papers

2023

On Unsupervised Uncertainty-Driven Speech Pseudo-Label Filtering and Model Calibration

ICASSP 2023accepted

Pseudo-label (PL) filtering forms a crucial part of Self-Training (ST) methods for unsupervised domain adaptation. Dropout-based Uncertainty-driven Self-Training (DUST) proceeds by first training a teacher model on source domain labeled data. Then, the teacher model is used to provide PLs for the un…

Cited by 5Source ↗Scholar ↗
2022

Detecting Dementia from Long Neuropsychological Interviews

EMNLP 2022finding

Neuropsychological exams are commonly used to diagnose various kinds of cognitive impairment. They typically involve a trained examiner who conducts a series of cognitive tests with a subject. In recent years, there has been growing interest in developing machine learning methods to extract speech a…

Cited by 3Source ↗PDF ↗Scholar ↗
2019

Incremental Transfer Learning in Two-pass Information Bottleneck Based Speaker Diarization System for Meetings

ICASSP 2019accepted

The two-pass information bottleneck (TPIB) based speaker diarization system operates independently on different conversational recordings. TPIB system does not consider previously learned speaker discriminative information while di-arizing new conversations. Hence, the real time factor (RTF) of TPIB…

Cited by 0Source ↗Scholar ↗