182 citations · 435 across the 38 of their papers we have counts for
10 papers · 1 filter
Audio Event and Scene Recognition: A Unified Approach using Strongly and Weakly Labeled Data
Anurag Kumar, Bhiksha Raj
In this paper we propose a novel learning framework called Supervised and Weakly Supervised Learning where the goal is to learn simultaneously from weakly and strongly labeled data…
Discovering Sound Concepts and Acoustic Relations In Text
Anurag Kumar, Bhiksha Raj, Ndapandula Nakashole
In this paper we describe approaches for discovering acoustic concepts and relations in text. The first major goal is to be able to identify text phrases which contain a notion of…
An Approach for Self-Training Audio Event Detectors Using Web Data
Benjamin Elizalde, Ankit Shah, Siddharth Dalmia +5
Audio Event Detection (AED) aims to recognize sounds within audio and video recordings. AED employs machine learning algorithms commonly trained and tested on annotated datasets. H…
Experiments on the DCASE Challenge 2016: Acoustic Scene Classification and Sound Event Detection in Real Life Recording
Benjamin Elizalde, Anurag Kumar, Ankit Shah +4
In this paper we present our work on Task 1 Acoustic Scene Classi- fication and Task 3 Sound Event Detection in Real Life Recordings. Among our experiments we have low-level and hi…
Features and Kernels for Audio Event Recognition
Anurag Kumar, Bhiksha Raj
One of the most important problems in audio event detection research is absence of benchmark results for comparison with any proposed method. Different works consider different set…
Classifier Risk Estimation under Limited Labeling Resources
Anurag Kumar, Bhiksha Raj
In this paper we propose strategies for estimating performance of a classifier when labels cannot be obtained for the whole test set. The number of test instances which can be labe…