Dr. Shikha Tripathi Profile

Dr. Shikha Tripathi

at PES Univ

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Proceedings Article | 1 May 2022 Paper

Detection of voice disability and its severity in children

Mohina Ahmadi, Pavani Mullapudi, Shreyashri Athani, Shikha Tripathi

Proceedings Volume 12171, 121710S (2022) https://doi.org/10.1117/12.2631479

KEYWORDS: Digital filtering, Signal processing, Acoustics, Pathology, Feature extraction, Error analysis, Fourier transforms

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Voice Disability is one of the common disabilities experienced by children. Speech being the major mode of communication, it is important to rectify the voice-related problems at an early stage in life. Painful endoscopic techniques like laryngoscopy are used by doctors to identify the voice disability. In this work, an algorithm is devised to measure the severity of voice disability in children using signal processing techniques. Spectrogram and curve fitting techniques are used to detect voice disability. The normal and pathological curve fitted functions are passed through an adaptive signal processing system. Correlation between the normal function and tuned pathological function is obtained which is used to determine the severity of the disability. The reported work on this topic is language-dependent and uses machine learning algorithms that need large databases. In this work, adaptive signal processing techniques and the use of voice acoustic parameters are explored. Sound samples used are vowel sounds that are independent of the language and a range has been assigned to quantify the severity of the disability.

Proceedings Article | 1 May 2022 Paper

Digital watermarking and tamper detection in speech signal using blind detection

Sharvari ., Vaishnavi D V, Dhanalakshmi R, Shikha Tripatha

Proceedings Volume 12171, 1217118 (2022) https://doi.org/10.1117/12.2631575

KEYWORDS: Digital watermarking, Signal detection, Modulation, Quantization, Signal processing, Statistical analysis, Detection and tracking algorithms, Discrete wavelet transforms, Network security

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Advancement of digital signal processing and networking has raised many security and copyright concerns, thus it is very important to protect the authentication of digital data. In this work, an audio watermarking algorithm has been proposed which can be efficiently used for tamper detection and is also robust against reasonable attacks. Also, the watermarks are inaudible. The proposed algorithm can easily detect tampering as the watermarks are embedded at each frame without causing any audio degradation. In the proposed technique, first the audio signal is compressed using Graph Based Transform (GBT), for which watermarks are embedded into Line Spectral coefficients (LSFs) that are derived from linear prediction (LP) analysis with dither modulation-quantization index modulation (DM-QIM). Watermarks thus embedded in all frames are not only inaudible to the Human auditory system but also potentially provide robustness against meaningful attacks. This work also focuses on Blind tamper detection which is made effortless due to the proposed embedding algorithm. To measure the robustness of the algorithm, general processing of watermarked signals was done along with fragility testing. Quality of the audio was measured using Perceptual Evaluation of Speech Quality (PESQ) and Short-time objective intelligibility (STOI). The maximum PESQ score and STOI score of 2.8781 and 0.8150 respectively was observed without any attack on the audio signal. Tamper detection and quality measurement are the major contributions of this work. Detailed metric evaluation for attacks such as Scaling, Resampling, Filtering, Compression and Addition of White Gaussian noise (AWGN) has been computed and compared. The proposed technique makes tamper identification easier and gives framewise security.

Proceedings Article | 20 January 2021 Paper

Robust and imperceptible digital speech watermarking

Akanksha J. N., Diya Dhiraj, Hemanth Reddy, Shikha Tripathi

Proceedings Volume 11719, 117190T (2021) https://doi.org/10.1117/12.2589645

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The concept of Speech watermarking has risen to be an efficient and promising solution to safeguard speech signals in today’s world of swiftly advancing communication technologies. In this paper, Robust Principal Component Analysis (RPCA) and Formant Manipulation (FM) have been used to embed the watermark into the host speech signal. RPCA involves obtaining the sparse component of the speech signal for accurate embedding, extraction of the watermark and FM involves modifying the formants by exploiting the properties of Line Spectral Frequencies (LSFs). A non-blind watermark detection scheme has been proposed to detect the watermark which demonstrates better stability and accuracy. Results of performance evaluation reveal that the proposed technique is robust and the watermark embedded is imperceptible. Also, the robustness of the method is verified by testing against several speech processing attacks.

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