Please use this identifier to cite or link to this item: http://hdl.handle.net/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://hdl.handle.net/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
metadata.dc.description.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, проиндексированные в SCOPUS и WoS CC

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