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AI BOT: An Intelligent Personal Assistant

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Proceeding of the International Conference on Computer Networks, Big Data and IoT (ICCBI - 2018) (ICCBI 2018)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 31))

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Abstract

Intelligent Personal Assistants (IPA) such as Google’s Assistant, Apple’s Siri and Microsoft’s Cortana excels in their natural language user interface. Still there is a need for single bundled IPA with multi-functionalities is increasing day by day. This paper presents the design and development of an artificial Intelligent personal assistant (AIPA), an open end-to-end web service application which receives queries in the form of voice and text and responds with natural language. The paper emphasizes on the implementation of different ways of interacting with a personal assistant and incorporating various functionalities which aren’t found in any of the existing virtual assistants with the help of several AI algorithms and open-source tools. Understanding context is important for any AI and increase in the context leads to the effective handling of open-ended requests. Unlike commercial products, this AI bot uses open ended requests than specific tasks to provide multifunctional to artificial brain.

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References

  1. Coehoorn, R.M., Jennings, N.R.: Learning about the opponent’s preferences to make effective multi-issue negotiation trade-os. In: Proceedings of the 6th International Conference on Electronic Commerce, pp. 59–68. ACM (2004)

    Google Scholar 

  2. Chao, L., Tao, J., Yang, M., Li, Y., Wen, Z.: Audio visual emotion recognition with temporal alignment and perception attention. arXiv preprint arXiv:1603.08321 (2016)

  3. ABI Research: Wearable Computing Devices, Like Apple iWatch, Will Exceed 485 Million Annual Shipments by 2018. https://www.abiresearch.com/press/wearablecomputing-devices-like-apples-iwatch-will (2013)

  4. Hearst, M.A.: ‘Natural’ search user interfaces. Commun. ACM 54(11), 60–67 (2011)

    Article  Google Scholar 

  5. Siegler, M.G.: Apple’s Massive New Data Center Set To Host Nuance Tech. http://techcrunch.com/2011/05/09/applenuance-data-center-deal/

  6. Huggins-Daines, D., Kumar, M., Chan, A., Black, A.W., Ravishankar, M., Rudnicky, A.I.: Pocketsphinx: a free, real-time continuous speech recognition system for hand-held devices. In: 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 Proceedings, vol. 1, p. I. IEEE (2006)

    Google Scholar 

  7. Povey, D., Ghoshal, A., Boulianne, G., Burget, L., Glembek, O., Goel, N., Hannemann, M., Motlicek, P., Qian, Y., Schwarz, P., Silovsky, J., Stemmer, G., Vesely, K.: The Kaldi speech recognition toolkit. In: IEEE 2011 Workshop on Automatic Speech Recognition and Understanding. IEEE Signal Processing Society (2011)

    Google Scholar 

  8. Rybach, D., Hahn, S., Lehnen, P., Nolden, D., Sundermeyer, M., Tuske, Z., Wiesler, S., Schluter, R., Ney, H.: RASR - the RWTH Aachen University Open Source Speech Recognition Toolkit (2011)

    Google Scholar 

  9. Seide, F., Li, G., Yu, D.: Conversational speech transcription using context-dependent deep neural networks. In: Interspeech, pp. 437–440 (2011)

    Google Scholar 

  10. Ferrucci, D., Brown, E., Chu-Carroll, J., Fan, J., Gondek, D., Kalyanpur, A.A., Adam Lally, J., Murdock, W., Nyberg, E., Prager, J., Schlaefer, N., Welty, C.: Building Watson: an overview of the DeepQA project. AI Mag. 31(3), 59–79 (2010)

    Google Scholar 

  11. Bay, H., Tuytelaars, T., Gool, L.V.: Surf: speeded up robust features. In: Computer Vision–ECCV 2006, pp. 404–417. Springer (2006)

    Google Scholar 

  12. Hinton, G., Deng, L., Dong, Yu., Dahl, G., Mohamed, A.R., Jaitly, N., Senior, A., Vanhoucke, V., Nguyen, P., Sainath, T., Kingsbury, B.: Deep neural networks for acoustic modeling in speech recognition. Signal Process. Mag. 29, 82–97 (2012)

    Article  Google Scholar 

  13. Tckstrm, O., Das, D., Petrov, S., McDonald, R., Nivre, J.: Token and type constraints for cross-lingual part-of-speech tagging. Trans. Assoc. Comput. Linguist. 1, 1–12 (2013)

    Article  Google Scholar 

  14. David Forney Jr., G.: The Viterbi algorithm. Proc. IEEE 61(3), 268–278 (1973)

    Article  MathSciNet  Google Scholar 

  15. Dahl, G.E., Yu, D., Deng, L., Acero, A.: Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition. IEEE Trans. Audio Speech Lang. Process. 20(1), 30–42 (2012)

    Article  Google Scholar 

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Authors and Affiliations

  1. SRM Institute of Science and Technology, Kattankulathur, Chennai, India

    A. Shanthini, Chirag Prasad Rao & G. Vadivu

Authors
  1. A. Shanthini
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  2. Chirag Prasad Rao
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  3. G. Vadivu
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Corresponding author

Correspondence to A. Shanthini .

Editor information

Editors and Affiliations

  1. Department of CSE, Vaigai College of Engineering, Melur, India

    A. Pasumpon Pandian

  2. Department of Engineering, University of the Ryukyus, Okinawa, Japan

    Tomonobu Senjyu

  3. Edith Cowan University (ECU), Joondalup, WA, Australia

    Syed Mohammed Shamsul Islam

  4. Department of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA

    Haoxiang Wang

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Shanthini, A., Rao, C.P., Vadivu, G. (2020). AI BOT: An Intelligent Personal Assistant. In: Pandian, A.P., Senjyu, T., Islam, S.M.S., Wang, H. (eds) Proceeding of the International Conference on Computer Networks, Big Data and IoT (ICCBI - 2018). ICCBI 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 31. Springer, Cham. https://doi.org/10.1007/978-3-030-24643-3_66

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  • DOI: https://doi.org/10.1007/978-3-030-24643-3_66

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-24642-6

  • Online ISBN: 978-3-030-24643-3

  • eBook Packages: EngineeringEngineering (R0)

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