Abstract
With the rapid development of modern computer technology, the communication between man and machine is becoming more frequent. A large amount of data is needed to input when people use Microsoft Excel software in the fields of account, office, finance, hospital, etc. This paper presents a recognition method of naming speech as input for Excel table. In this system, we use the characteristics of the name as a basic speech unit by using the Mel Frequency Coefficients (MFCC) as the feature parameters. Moreover, we use the Hidden Markov model (HMM) as the basis to train the acoustic models of this environment. The HMM can ease the mismatch caused by the identification of the test environment and training environment, which can improve the recognition rate further. Finally, experiments show that this system has good recognition and input function. This study establishes the foundation for future development of the method of application system.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Yan Y (2013) The latest application of linguistic acoustics. Chin J Acoust 35(2):241–247
Cai L, Huang D, Cai R (2003) Technology and application of modern speech. Tsinghua University Press, Beijing
Kim DS, Lee SY, Kil RM (1999) Auditory processing of speech signals for robot speech recognition in real-world noisy environments. IEEE Trans Speech Audio Process 7(1):55–69
Chen S, Jiang Q (1993) Evaluation of speech technology for enhancing performance of man–machine systems. Space Med Med Eng 6(1):31–38
JinPu Xu, YePing Zhu (2015) The price of agricultural products information acquisition method based on speech recognition. Sci Agric Sinica 48(3):449–459
Wang Z, Tang Y, Han P (2012) Using voice recognition of forest road detection method. Comput Eng Appl 48(30)
ZiHao Xu, TengFei Zhang (2012) Design of intelligent speech recognition and home furnishing system based on wireless sensor network. Comput Measur Control 20(1):180–182
Chen J, Zhang L, Wu X (2007) Feature extraction based on wavelet packet-LPCC in speaker recognition. J Nanjing Univ Post Telecommun Nat Sci 27(6):54–56
Shao Y, Liu B, Li Z (2002) Speaker recognition system based on MFCC and weighted vector quantization. Comput Eng Appl 127–128
Arslan LM, Hansen JHL (1997) Frequency characteristics of foreign accented speech. In: Proceedings of international conference on acoustics, speech and signal processing, vol 97, pp 1123–1127 (1997)
Myers C, Rabiner L (1981) Connected digit recognition using a level building DTW algorithm. IEEE Trans ASSP 29:351–363
Rabiner LR (1986) An introduction to hidden markov models. IEEE Acoust Speech Signal Process Mag 1:5–16
Li SZ, Guo-dong G (2000) Content-based audio classification and retrieval using SVM learning. In: Proceedings of the 1st IEEE pacific-rim conference on multimedia
Zhang LM (1994) Model and application of artificial neural network. Fudan University Press, Shang Hai, pp 23–123
Abu EI-Yazeed MF, EI Gamal MA, EI Ayadi MMH (2007) On the determination of optimal model order for GMM—based text-independent speaker identification. J Appl Sig Process 8:1078–1087
Acknowledgments
This paper was partially supported by The Scientific Innovation program (13ZZ115), National Natural Science Foundation (61374040, 61203143), Hujiang Foundation of China (C14002), Graduate Innovation program of Shanghai (54-13-302-102).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Meng, X., Wang, C. (2016). Interactive Speech Recognition Based on Excel Software. In: Jia, Y., Du, J., Li, H., Zhang, W. (eds) Proceedings of the 2015 Chinese Intelligent Systems Conference. Lecture Notes in Electrical Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48365-7_23
Download citation
DOI: https://doi.org/10.1007/978-3-662-48365-7_23
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-48363-3
Online ISBN: 978-3-662-48365-7
eBook Packages: EngineeringEngineering (R0)