Interra Systems, Inc.

Manik Gupta

Shailesh Kumar

Abhishek Kumar Tiwary

Anuj Verma

Prabhanjana Kumar Nallani

Praveen Kumar Tiwari

Ramandeep Singh Sandhu

Kulbhushan

Vivek Koul

Niraj Sinha

Rohit Gupta

Hemant Kumar Gangwar

A system and a method for detecting a simulated Emergency Alert Signal (EAS) are disclosed. The method includes detecting, by a first detector, one or more tones in a plurality of audio frames. Further, the method includes detecting, by a second detector, one or more beeps in the plurality of audio frames. Thereafter, the method includes detecting, by a third detector, at least one emergency word in the plurality of audio frames based at least on the detected one or more tones or the detected one or more beeps, and thereby detecting the simulated EAS.

System and method for detecting a simulated emergency alert signal (EAS)

The disclosed embodiments relates to methods and systems for performing a content verification in a video content. The method includes identification of one or more random access points in the video content. Thereafter, one or more work units are created based on the identified one or more random access points. The method further includes processing of the one or more work units by one or more processing units simultaneously, and determining one or more errors in each of the one or more work units while the decoding. The one or more determined errors in each of processed one or more work units are then merged with each other. A verification report is generated based on at least the merging.

Methods and systems for file based content verification using multicore architecture

A method and system for detecting and quantifying blockiness in a video file is disclosed. The video file is a file that has been decompressed by using standard DCT algorithms. The method includes segmenting each frame of the video file into multiple blocks. The method also involves comparing the intensity gradients of each block with one or more threshold values. The one or more threshold values represent predefined intensity variation characteristics. Further, the method includes determining the intensity variation parameters of each block, based on the comparison. Thereafter, a blockiness index is calculated for each block, after which a blockiness value is calculated for each frame. Finally, a blockiness level is assigned to each frame, based on its blockiness value. The blockiness level is a comparative measure of the blockiness of a frame that represents the blockiness content in the frame.

Method and system to detect and quantify blockiness in video files

A method for automatically verifying one or more features of file-based media content () is disclosed. This file-based media content includes one or more media content files. The method includes customizing () a test plan on the basis of the one or more features. Customizing the test plan includes creating, modifying or utilizing at least one media content check of one or more media content checks. A media content check verifies at least one feature of the one or more features of the file-based media content. Further, the method includes verifying () the one or more features, based on the customized test plan. The method also includes documenting () the results obtained from the verification of the one or more features.

Method for verification of file-based media content

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Delhi, India

Manik Gupta