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http://elar.urfu.ru/handle/10995/101806
Title: | A Question Detection Algorithm for Text Analysis |
Authors: | Chung, T. D. Son, H. H. Khalyasmaa, A. |
Issue Date: | 2020 |
Publisher: | Association for Computing Machinery |
Citation: | Chung T. D. A Question Detection Algorithm for Text Analysis / T. D. Chung, H. H. Son, A. Khalyasmaa. — DOI 10.1145/3385209.3385230 // ACM International Conference Proceeding Series. — 2020. — P. 61-65. |
Abstract: | In this paper, an effective question detection algorithm for Vietnamese text analysis is proposed. The proposed algorithm takes an audio file as input, converts its speech to text, and returns question detection result. This is extremely useful for a text analyzer to determine if a given sentence generated from an audio file is a question or not, particularly in chatbot or voicebot systems where very often there are needs for automatic replies to questions queried by users. The algorithm uses two tiers of question words and a customized question phrases to achieve 88.64 % accuracy on a sub-dataset of 176 questions prepared based on FPT Open Speech Dataset. © 2020 ACM. |
Keywords: | ALGORITHM APPLICATION PROGRAMMING INTERFACE (API) CHATBOT DETECTION QUESTION SPEECH-TO-TEXT (STT) TEXT ANALYSIS VOICEBOT AUDIO SYSTEMS AUDIO FILES CHATBOT DETECTION ALGORITHM TEXT ANALYSIS TEXT ANALYZERS TWO TIERS VIETNAMESE SIGNAL DETECTION |
URI: | http://elar.urfu.ru/handle/10995/101806 |
Access: | info:eu-repo/semantics/openAccess |
SCOPUS ID: | 85086138149 |
PURE ID: | 13164037 d21d75be-751b-4002-910e-8481f7c89f18 |
ISBN: | 9781450376594 |
DOI: | 10.1145/3385209.3385230 |
Sponsorship: | The authors would thank FPT University and Ural Federal University for supporting this research. In addition, the authors would thank the students: Nguyen Khuong Quan, Tran Viet Thai, Le Sy Thanh Long in SE1402 class, FPT University for their partial support this research. |
Appears in Collections: | Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC |
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