Department Of Civil Engineering

Forces in Mechanics

Fatigue in a class of viscoelastic solids

While Self-Supervised Learning has helped reap the benefit of the scale from the available unlabeled data, the learning paradigms are continously being bettered. We present a new pre-training strategy named ccc-wav2vec 2.0, which uses clustering and an augmentation based cross-contrastive loss as its self-supervised objective. Through the clustering module we scale down the influence of those negative examples that are highly similar to the positive. The Cross-Contrastive loss is computed between the encoder output of the original sample and the quantizer output of its augmentation, and vice-versa, bringing robustness to the pre-training strategy. ccc-wav2vec 2.0 achieves upto 15.6% and 12.7% relative WER improvement over the baseline wav2vec 2.0 on the test-clean and test-other sets respectively of LibriSpeech, without the use of any language model. The proposed method also achieves upto 14.9% relative WER improvement over the baseline wav2vec 2.0, when fine-tuned on Switchboard data. © 2023 IEEE.

World University root node

Department of Electrical Engineering

2022 IEEE Spoken Language Technology Workshop, SLT 2022 - Proceedings

CCC-WAV2VEC 2.0: Clustering AIDED Cross Contrastive Self-Supervised Learning of Speech Representations

This paper reports an experimental study of spray characteristics in rotary slinger atomizers using different laser diagnostic tools. The main objective of the present study is to investigate the effect of size of the slinger orifices on liquid breakup dynamics and droplet size distribution over a wide range of rotational speed (5000–45,000 rpm) and liquid flow rates (0.2–2 lpm). Three different slinger discs having the same number of orifices but different sizes (d0 = 1, 1.5, and 2 mm) are considered. The primary liquid breakup visualization is achieved using volumetric laser-induced fluorescence (VLIF) technique; whereas, the droplet size is measured by interferometric laser imaging for droplet sizing (ILIDS) technique. The results demonstrate critical role of orifice size on liquid breakup mode and droplet size up to rotational speed about 30,000 rpm, beyond which the aerodynamic force dominates the atomization process such that neither the orifice size nor rate of rotation has strong influence. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Department of Mechanical Engineering

Lecture Notes in Mechanical Engineering

A Parametric Study on Rotary Slinger Spray Characteristics Using Laser Diagnostics

Department of Metallurgical and Materials Engineering

GENERAL

Department Of Physics

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras