Titlebook: Speech and Computer; 25th International C Alexey Karpov,K. Samudravijaya,S. R. Mahadeva Pras Conference proceedings 2023 The Editor(s) (if

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Ashwini Dasare,Amartya Roy Chowdhury,Aditya Srinivas Menon,Konjengbam Anand,K. T. Deepak,S. R. M. Pr indicates, our chief concern is with (i) nondifferentiable mathematical programs, and (ii) two-level optimization problems. In the first half of the book, we study basic theory for general smooth and nonsmooth functions of many variables. After providing some background, we extend traditional (diff

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Ankita,Shambhavi,Syed Shahnawazuddin indicates, our chief concern is with (i) nondifferentiable mathematical programs, and (ii) two-level optimization problems. In the first half of the book, we study basic theory for general smooth and nonsmooth functions of many variables. After providing some background, we extend traditional (diff

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Analysing Breathing Patterns in Reading and Spontaneous Speech. By comparing the performance across speakers, speech categories, and speech-breathing categories, we aim to uncover the factors influencing SBreathNet’s effectiveness when applied to these two types of speech signals.

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Analysis of a Hinglish ASR System’s Performance for Fraud Detectionother equally important aspect while doing deployment of speech technology based products is that it is rather difficult to know if the performance of an ASR engine is adequate for its output to be used for a down-stream task. In this paper, we present our study of how the performance of an ASR engi

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Improvements in Language Modeling, Voice Activity Detection, and Lexicon in OpenASR21 Low Resource Lxicon from public text is beneficial for languages where the out-of-vocabulary rate is high, and outline conditions for reducing the WER. Adding an attention layer to the TDNN (time delay neural net) based voice activity detector reduced the WER for 17 out of the 18 languages. With all the improveme

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