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Titlebook: Speech and Computer; 22nd International C Alexey Karpov,Rodmonga Potapova Conference proceedings 2020 Springer Nature Switzerland AG 2020 a

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Iustina Andronic,Ludwig Kürzinger,Edgar Ricardo Chavez Rosas,Gerhard Rigoll,Bernhard U. Seeber muscles, reduces the work of breathing, mitigates dyspnea and fatigue, finally increasing minute ventilation. Clinically, NIV represents the gold standard for the initial management of hypercapnic respiratory failure, acute respiratory failure due to cardiogenic pulmonary edema, and any condition y
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Andrei Andrusenko,Aleksandr Laptev,Ivan Medennikov muscles, reduces the work of breathing, mitigates dyspnea and fatigue, finally increasing minute ventilation. Clinically, NIV represents the gold standard for the initial management of hypercapnic respiratory failure, acute respiratory failure due to cardiogenic pulmonary edema, and any condition y
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Dealing with Newly Emerging OOVs in Broadcast Programs by Daily Updates of the Lexicon and Languageion into the lexicon of the transcription system and c) proper tuning of the language model. Experimental evaluation is performed on an extensive data-set compiled from various Czech broadcast programs. This data was produced by a real transcription platform over the course of 300 days in 2019. Deta
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Automatic Prediction of Word Form Reduction in Russian Spontaneous Speech,ceived different lists using different algorithms, but the adjective and parenthetical word were in both of them. Thus, we can conclude that adjectives and parenthetical words are likely to be reduced more often than other parts of speech.
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Emotion Recognition and Sentiment Analysis of Extemporaneous Speech Transcriptions in Russian,implemented using Bag-of-Words, Word2Vec, FastText and BERT methods. Investigated machine classifiers include Support Vector Machine, Random Forest, Naive Bayes and Logistic Regression. To the best of our knowledge, this is the first study of sentiment analysis and emotion recognition for both extem
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Lipreading with LipsID,hanism. This paper presents results from experiments with the LipNet network by re-implementing the system and comparing it with and without LipsID features. The results show a promising path for future experiments and other systems. The training and testing process of neural networks used in this w
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