Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Haridas, Arul Valiyavalappila; * | Marimuthu, Ramalathab | Sivakumar, Vaazi Gangadharanc
Affiliations: [a] ECE, Thejus Engineering College, Thrissur, India | [b] ECE, Kumaraguru College of Technology, Coimbatore, India | [c] ECE, Sathyabama University, Chennai, India
Correspondence: [*] Corresponding author: Arul Valiyavalappil Haridas, ECE, Thejus Engineering College, Thrissur, India. E-mail: arul.vh01@gmail.com.
Abstract: Recognition of human speech has long been an intriguing issue among artificial intelligence and processing researchers. Speech is the most crucial and essential method of communication among the human beings. Several research efforts have been prepared in the field of speech recognition in the previous decades. Accordingly, a survey of speech recognition strategies suitable for human identification is discussed in this study. The main motivation of this survey is to explore the existing speech recognition strategies so that the researchers can include all the necessary metrics in their works in this domain and the limitations in the existing ones can be overcome. In this review, diverse issues included in speech recognition methodologies is distinguished and distinctive speech recognition procedures were studied to discover which qualities is tended to in a given system and which is disregarded. Hence, we offer a detailed survey of 50 methods from standard publishers from the year of 2000 to 2015. Here, we categorize the research based on three dissimilar perspectives, like techniques utilized, applications and parameter measures. In addition, this study gives an elaborate idea about speech recognition techniques.
Keywords: Speech recognition, artificial intelligence, hidden Markov Model, knowledge based approach, fuzzy logic
DOI: 10.3233/KES-180374
Journal: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 22, no. 1, pp. 39-57, 2018
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl