Citation: Proceedings of the 2018 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 15, pages 165–168 (2018)
Abstract. This paper examines the perspectives of intonation processing for automatic keyword extraction. Based on a discourse intonation model from D. Brazil, automatic tone pattern recognition in speech stream is performed. It is shown that automatic classification of tone patterns can be done using simple polynomials and correlation. The original software tool PitchKeywordExtractor (PKE) was applied to academic discourse (on-line lectures) to extract keywords. The results were compared to the output of popular tools for speech analytics: VoiceBase and IBM Watson. All the records were processed also with Praat software and annotated by human experts. Experiments show that none of the automatic systems outperforms the others and PKE, VoiceBase and IBM Watson have the identical error rates with respect to human expert opinion. It motivates further research and supports the tendency to integrate intonation and, more generally, prosody processing in automatic keyword extraction.
- Polykarpos Meladianos, Antoine J-P Tixier, Giannis Nikolentzos, and Michalis Vazirgiannis, “Real-time keyword extraction from conversations,” EACL 2017, p. 462, 2017.
- David O. Johnson and Okim Kang, “Automatic prosodic tone choice classification with brazil’s intonation model,” International Journal of Speech Technology, vol. 19, no. 1, pp. 95–109, Mar 2016.
- Anton Batliner and Bernd Möbius, Prosodic Models, Automatic Speech Understanding, and Speech Synthesis: Towards the Common Ground?, pp. 21–44, Springer Netherlands, Dordrecht, 2005.
- Elizabeth Shrieberg and Andreas Stolcke, “Prosody modeling for automatic speech recognition and understanding,” 2002.
- Yurij Lezhenin, Artyom Zhuikov, Natalia Bogach, Elena Boitsova, and Evgeny Pyshkin, “Pitchkeywordextractor: Prosody-based automatic keyword extraction for speech content,” in Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, FedCSIS 2017, Prague, Czech Republic, September 3-6, 2017., 2017, pp. 265–269.
- Alan Darmasaputra Chowanda, Albert Richard Sanyoto, Derwin Suhartono, and Criscentia Jessica Setiadi, “Automatic debate text summarization in online debate forum,” Procedia Computer Science, vol. 116, no. Supplement C, pp. 11 – 19, 2017, Discovery and innovation of computer science technology in artificial intelligence era: The 2nd International Conference on Computer Science and Computational Intelligence (ICCSCI 2017).
- Slobodan Beliga, Ana Mestrovic, and Sanda Martincic-Ipsic, “Selectivity-based keyword extraction method.,” Int. J. Semantic Web Inf. Syst., vol. 12, no. 3, pp. 1–26, 2016.
- Slobodan Beliga, “Keyword extraction techniques,” 2016.
- Yan Ying, Tan Qingping, Xie Qinzheng, Zeng Ping, and Li Panpan, “A graph-based approach of automatic keyphrase extraction,” Procedia Computer Science, vol. 107, no. Supplement C, pp. 248 – 255, 2017, Advances in Information and Communication Technology: Proceedings of 7th International Congress of Information and Communication Technology (ICICT2017).
- Santosh Kumar Bharti and Korra Sathya Babu, “Automatic keyword extraction for text summarization: A survey,” CoRR, vol. abs/1704.03242, 2017.
- Aytuğ Onan, Serdar Korukoğlu, and Hasan Bulut, “Ensemble of keyword extraction methods and classifiers in text classification,” Expert Systems with Applications, vol. 57, no. Supplement C, pp. 232 – 247, 2016.
- Yanzhang He, Brian Hutchinson, Peter Baumann, Mari Ostendorf, Eric Fosler-Lussier, and Janet B. Pierrehumbert, “Subword-based modeling for handling oov words inkeyword spotting,” 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 7864–7868, 2014.
- D. Sowmya and J.I. Sheeba, “Keyword extraction using particle swarm optimization,” Procedia Computer Science, vol. 85, no. Supplement C, pp. 183 – 189, 2016, International Conference on Computational Modelling and Security (CMS 2016).
- Janet Pierrehumbert, Prosody, intonation, and speech technology, p. 257–280, Studies in Natural Language Processing. Cambridge University Press, 1993.
- GraÅijyna Demenko, “Intonation processing for speech technology przetwarzanie intonacji na potrzeby technologii mowy,” 2012.
- Mustafa Sönmez, Elizabeth Shriberg, Larry Heck, and Mitchel Weintraub, “Modeling dynamic prosodic variation for speaker verification,” 01 1998.
- M. A. K. Halliday and William S. Greaves, Intonation in the grammar of English / by M. A. K. Halliday and William S. Greaves, Equinox Pub London ; Oakville, CT, 2008.
- David Brazil et al., Discourse intonation and language teaching., ERIC, 1980.
- Miriam P. Germani and Lucia Rivas, “Discourse intonation and systemic functional phonology,” Colombian Applied Linguistics Journal, vol. 13, no. 2, pp. 100–113, 2011.
- Dorothy M Chun, Discourse Intonation in L2 – From Theory and Research to Practice, 01 2002.
- Malcolm Coulthard and David Brazil, The place of intonation in the description of interaction, Linguistic Agency University of Trier, 1981.