Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item The Role of Cryptography in Cryptocurrency(Institute of Electrical and Electronics Engineers Inc., 2021) Gupta, S.P.; Gupta, K.; Chandavarkar, B.R.In today's world of digital media, people are mainly sharing all of their resources via digital platforms. Today, in almost all regions across the globe, the physical exchange of money is becoming less in practice. People are more flexible with buying and paying for their necessities via digital platforms rather than exchanging physical money. Cryptocurrency, the new global money for the internet age, is also a medium of exchange similar to other currencies. Still, here, the sole purpose of the exchange is via digital means. How secure is your cryptocurrency? How anonymous are users of cryptocurrencies? Since the currency is digital, it is more prone to attacks, data theft, and money. Here comes the role of cryptography. Cryptography is an essential mechanism for securing information in computer systems. Without cryptography, cryptocurrency is just a central hub for attackers and scammers. Cryptocurrency requires cryptography for mainly two purposes; to secure the transactions and to verify these transfers. This paper discusses the types of cryptographic techniques used in cryptocurrencies, studies their characteristics, and explores the working of these techniques. © 2021 IEEE.Item Recognition of Fricative Phoneme based Hindi Words in Speech-to-Text System using Wav2Vec2.0 Model(Institute of Electrical and Electronics Engineers Inc., 2022) Gupta, S.P.; Spoorthy, V.; Koolagudi, S.G.In this work, we have discussed issues with Microsoft's state-of-the-art Speech-to-Text (STT) system. Two key issues have been identified: recognition of Hindi words starting with the fricative phoneme (/ha/) and recognition power of the system with background noise. The solution for correctly identifying the unrecognized Hindi fricative phoneme is by training the Wav2Vec2.0 model on the OpenSLR Hindi dataset. The evaluation of the proposed model is given by the performance metric Char-acter Error Rate (CER). To test the performance of the proposed model, 20 fricative words in both clean and noisy conditions are fed to the trained model. The second issue of handling noisy speech samples is resolved using an amplitude-based automatic noise detection method. The results achieved from the proposed model are observed to be better than the state-of-the-art STT model when trained with and without the language model in terms of CER in clean conditions. © 2022 IEEE.Item Noise Cancellation by Fast Fourier Transform for Wav2Vec2.0 based Speech-to-Text System(Institute of Electrical and Electronics Engineers Inc., 2023) Gupta, S.P.; Spoorthy, V.; Koolagudi, S.G.Speech-To-Text (STT) systems are a part of the Speech Recognition domain in which speech is given as input, and it generates the transcript. The input speech sometimes disrupts the STT system and generates incorrect transcripts because of background noise. In this work, we have discussed a Fast Fourier Transform (FFT) based noise cancellation method for Hindi words with background noise and performed speech to text conversion using a fine-tuned and pre-trained Wav2Vec2.0 model. The background noise added to the audio samples is Gaussian white noise with three different intensity levels, 0.01, 0.03, and 0.05 units, indicated by the Gaussian distribution's standard deviation (STD). The model has been trained on the OpenSLR Hindi dataset. The proposed system is evaluated by the metric Character Error Rate (CER). The testing of the model is done using 20 Hindi words in both clean and noisy conditions. The results obtained proved that the noise cancellation was found effective in terms of CER, and on first level noise with an STD of 0.01, the CER is better after noise cancellation than its noisy counterpart. © 2023 IEEE.