RETRACTED ARTICLE: Automatic speech recognition systems: A survey of discriminative techniques

• Published in: Multimedia tools and applications Vol. 82; no. 9; pp. 13307 - 13339
• Main Authors: Kaur, Amrit Preet, Singh, Amitoj, Sachdeva, Rohit, Kukreja, Vinay
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.04.2023; Springer Nature B.V
• Subjects: Computer Communication Networks; Computer Science; Data Structures and Information Theory; Multimedia Information Systems; Special Purpose and Application-Based Systems; Deep learning; Feature extraction; Speech processing; Speech recognition; Acoustic modeling
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-022-13645-x

In the subject of pattern recognition, speech recognition is an important study topic. The authors give a detailed assessment of voice recognition strategies for several majority languages in this study. Over the last several decades, many researchers have contributed to the field of voice processing and recognition. Although there are several frameworks for speech processing and recognition, there are only a few ASR systems available for language recognition throughout the world. However, the data gathered for this research reveals that the bulk of the effort has been done to construct ASR systems for majority languages, whereas minority languages suffer from a lack of standard speech corpus. We also looked at some of the key issues for voice recognition in various languages in this research. We have explored various kinds of hybrid acoustic modeling methods required for efficient results. Because the success of a classifier is dependent on the removal of information during the feature separation phase, it is critical to carefully pick the value extraction techniques and classifiers.