Hybrid DNN-HMM-Based Approach for Telugu Language Speech Recognition by M. Rama Rajeswari, Suryakanth V. Gangashetty

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Telugu language hate speech detection using deep learning transformer models: Corpus generation and evaluation by Namit Khanduja, Nishant Kumar, Arun Chauhan

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Sentiment classification for telugu using transformed based approaches on a multi-domain dataset by Kannaiah Chattu, K. Adi Narayana Reddy, Sai babu veesam, Pardha Saradhi Chirumamilla, Vunnava Dinesh Babu, Krishna Prakash, Shonak Bansal, Mohammad Rashed Iqbal Faruque, K. S. Al-mugren

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Analysis and development of clinically recorded dysarthric speech corpus for patients affected with various stroke conditions by Oindrila Banerjee, K.V.N. Sita Mahalakshmi, M.V.S. Jyothi, D. Govind, U.K. Rakesh, A. Rajeev, K. Samudravijaya, Akhilesh Kumar Dubey, Suryakanth V. Gangashetty

“…The text read by patients and healthy controls comprises (a) five sustained vowels, (b) three words consisting of the plosive consonant and vowels, and (c) 10 phonetically rich sentences in Telugu language. A discriminative analysis is carried out using conventional Mel Frequency Cepstral Coefficients and Convolutional Neural Networks to quantify the perceptual variations in dysarthric speech of stroke patients and healthy controls. …”
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