Noisy signal identification from non-stationary audio signals

US9978392B2 · kind B2 · utility

Assignee

• Tata Consultancy Services Limited · IN

Inventors

• Arijit Ukil · Sherghati, IN
• Soma Bandyopadhyay · Sherghati, IN
• Chetanya Puri · Sherghati, IN
• Arpan Pal · Sherghati, IN
• Rituraj Singh · Sherghati, IN
• Ayan Mukherjee · Sherghati, IN
• Debayan Mukherjee · Sherghati, IN

Key dates

• Filing date: Mar 10, 2017
• Grant date: May 22, 2018
• Expiry date: Mar 10, 2037

Classification

• Technology area (CPC G): Physics
• CPC primary: G16H50/70
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Traditionally known classification methods of non-stationary physiological audio signals as noisy and clean involve human intervention, may involve dependency on particular type of classifier and further analyses is carried out on classified clean signals. However, in non-stationary audio signals a major portion may end up being classified as noisy and hence may get rejected which may cause missing of intelligence which could have been derived from lightly noisy audio signals that may be critical. The present disclosure enables automation of classification based on auto-thresholding and statistical isolation wherein noisy signals are further classified as highly noisy and lightly noisy through continuous dynamic learning.