Search Results for author:
Found 7 papers, 2 papers with code
Beyond the Labels: Unveiling Text-Dependency in Paralinguistic Speech Recognition Datasets
This paper critically evaluates the prevalent assumption that machine learning models trained on such datasets genuinely learn to identify paralinguistic traits, rather than merely capturing lexical features.
Strategies for improving low resource speech to text translation relying on pre-trained ASR models
This paper presents techniques and findings for improving the performance of low-resource speech to text translation (ST).
Detecting English Speech in the Air Traffic Control Voice Communication
The proposed English Language Detection (ELD) system is based on the embeddings from Bayesian subspace multinomial model.
A Bayesian Multilingual Document Model for Zero-shot Topic Identification and Discovery
In this paper, we present a Bayesian multilingual document model for learning language-independent document embeddings.
Learning document embeddings along with their uncertainties
We present Bayesian subspace multinomial model (Bayesian SMM), a generative log-linear model that learns to represent documents in the form of Gaussian distributions, thereby encoding the uncertainty in its co-variance.
Ranked #1 on
Topic Models
on 20 Newsgroups
An Empirical Evaluation of Zero Resource Acoustic Unit Discovery
Acoustic unit discovery (AUD) is a process of automatically identifying a categorical acoustic unit inventory from speech and producing corresponding acoustic unit tokenizations.
IIIT-H System for MediaEval 2014 QUESST
This paper mainly focuses on the experiments and analysis of the existing NS-DTW algorithm for various types of queries.
Ranked #29 on
Keyword Spotting
on QUESST
