Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Spontaneous Speech and Its Features Are Taken into Account When Creating Recognition Programs. |
| Συγγραφείς: |
Yergaliyev, Askhat, Sharipbay, Altynbek, Baibulekova, Lyailya |
| Πηγή: |
Ingénierie des Systèmes d'Information; Apr2023, Vol. 28 Issue 2, p443-450, 8p |
| Θεματικοί όροι: |
Research, Deep learning |
| Περίληψη: |
The relevance of the stated subject of this scientific research is determined by the numerous difficulties of spontaneous speech recognition due to the presence of a complex of unrelated factors, as well as the need to find the best ways to overcome them through recognition programs that are used in the development of a multilingual corpus. This research aims to identify and study the key features of spontaneous speech that should be considered when creating recognition programs. The basis of the methodological approach in this scientific study is a combination of methods combining a systematic analysis of the principles of building a multilingual corpus with an analytical study of the principles of operation of spontaneous speech recognition programs. In the course of this scientific study, results were obtained that indicate a significant increase in the practical efficiency of automatic speech recognition systems when introducing sound signal correction algorithms, which opens up additional opportunities for developing such software. In addition, the results of this scientific study clearly demonstrate the significant impact of the accuracy of the effects of speech recognition programs on the quality of development of multilingual corpora, which include relatively large volumes of texts. The practical significance of the results obtained in the course of this scientific work, as well as the conclusions formulated on their basis, lies in the possibility of their use in the development of a multilingual corpus and spontaneous speech recognition programs for their subsequent use in various information systems, to obtain results related to the need accurate decoding of automatic speech, taking into account all its characteristic features. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: |
Complementary Index |