Kajian Penelitian Pemrosesan Bunyi dan Aplikasinya pada Teknologi Informasi

Authors

  • Ranny Ranny Institut Teknologi Bandung
  • Iping Supriana Suwardi <em><span lang="IN"><em>Sekolah Teknik Elektro dan Informatika Institut Teknologi Bandung </em></span><span lang="EN-US"></span></em>
  • Tati Latifah Erawati Rajab <em><span lang="IN"><em>Sekolah Teknik Elektro dan Informatika Institut Teknologi Bandung </em></span><span lang="EN-US"></span></em>
  • Dessi Puji Lestari <em><span lang="IN"><em>Sekolah Teknik Elektro dan Informatika Institut Teknologi Bandung </em></span><span lang="EN-US"></span></em>

DOI:

https://doi.org/10.30595/juita.v7i1.3491

Keywords:

bunyi, suara, Smart Homes, pengenalan suara dan bunyi, ekstraksi ciri suara dan bunyi, MFCC.

Abstract

Hasil dari peneitian banyak digunakan dan dikembangkan pada aplikasi yang telah banyak dimanfaatkan pada kehidupan sehari-hari. Proses identifikasi bunyi menjadi salah satu penelitian yang banyak dilakukan. Identifikasi bunyi yang dilakukan oleh manusia berbeda satu sama lain. Misal pada suara detak jantung, pada pendengar umum, suara detak jantung tidak memiliki informasi apa pun terkait kesehatan, tapi jika suara detak jantung diperdengarkan pada ahli medik atau dokter, maka informasi yang diperoleh akan berbeda, dokter dapat mengidentifikasikan suara detak jantung dikaitkan dengan kondisi kesehatan jantung. Selain dalam bidang medis, bunyi juga dimanfaatkan pada aplikasi berbasis bunyi dan suara pada Smart Homes. Namun, sebelum mengkaji tentang aplikasi pada Smart Homes dan aplikasi lain maka akan dibahas beberapa teori dasar tentang bunyi dan suara, seperti: teori suara dan bunyi, noise pada data suara, serta ekstraksi ciri suara bunyi yang secara spesifik akan menjelaskan tentang Mel Frequency Cepstrum Coefficients (MFCC). Berdasarkan hasil kajian dapat dibuat kerangka kerja aplikasi yang dibuat. Kerangka kerja yang disusun merupakan kerangka kerja yang umum dilakukan pada aplikasi dan penelitian tentang penggunaan data suara dan bunyi. Selain itu kajian ini akan menjabarkan tentang lingkup penelitian bunyi dan suara yang telah banyak dilakukan. Melalui penjabaran tentang lingkup penelitian didapatkan peluang penelitian yang dapat dilakukan pada data bunyi dan suara serta tantangannya.

References

[1] R. L. Klevans, R.D. RodmanR. L. Klevans, R.D. Rodman 1997a. Voice Recognition. Artech House, Michigan University.

[2] Mihail Popescu et al.Mihail Popescu et al. 2008b. “An Acoustic Fall Detector System That Uses Sound Height Information to Reduce the False Alarm Rate.” In 30th Annual International IEEE EMBS Confercence, Vancouver, British Columbia, Canada, 4628–31.

[3] Jianfeng Chen et al.Jianfeng Chen et al. 2005c. “Bathroom Activity Monitoring Based on Sound BT - Pervasive Computing.” In eds. Hans -W. Gellersen, Roy Want, and Albrecht Schmidt. Berlin, Heidelberg: Springer Berlin Heidelberg, 47–61.

[4] Oliver Amft, Mathias Stäger, Paul Lukowicz, Gerhard TrösterOliver Amft, Mathias Stäger, Paul Lukowicz, Gerhard Tröster 2005d. “Analysis of Chewing Sounds for Dietary Monitoring.” : 56–72.

[5] S Anderson et al.S Anderson et al. 1999e. “Recognition of Elderly Speech and Voice-Driven Document Retrieval.” In 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258), , 145–48 vol.1.

[6] Pei-Yu (Peggy) Chi, Jen-Hao Chen, Hao-Hua Chu, Jin-Ling LoPei-Yu (Peggy) Chi, Jen-Hao Chen, Hao-Hua Chu, Jin-Ling Lo 2008f. “Enabling Calorie-Aware Cooking in a Smart Kitchen.” In Proceedings of the 3rd International Conference on Persuasive Technology, PERSUASIVE ’08, Berlin, Heidelberg: Springer-Verlag, 116–27.

[7] Eva Ganglbauer, Geraldine Fitzpatrick, Georg MolzerEva Ganglbauer, Geraldine Fitzpatrick, Georg Molzer 2012g. “Creating Visibility: Understanding the Design Space for Food Waste.” In Proceedings of the 11th International Conference on Mobile and Ubiquitous Multimedia, MUM ’12, New York, NY, USA: ACM, 1:1--1:10.

[8] Azusa Kadomura et al.Azusa Kadomura et al. 2014h. “Persuasive Technology to Improve Eating Behavior Using a Sensor-Embedded Fork.” In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp ’14, New York, NY, USA: ACM, 319–29.

[9] J M ValinJ M Valin 2007i. “On Adjusting the Learning Rate in Frequency Domain Echo Cancellation With Double-Talk.” IEEE Transactions on Audio, Speech, and Language Processing 15(3): 1030–34.

[10] Maunder D., Ambikairajah E., Epps J.Maunder D., Ambikairajah E., Epps J. 2008j. “Dual-Microphone Sounds of Daily Life Classification for Telemonitoring in a Noisy Environment.” Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 2008(1): 4636–39.

[11] A Harma, M F McKinney, J SkowronekA Harma, M F McKinney, J Skowronek 2005k. “Automatic Surveillance of the Acoustic Activity in Our Living Environment.” In 2005 IEEE International Conference on Multimedia and Expo, , 4 pp.

[12] T Kojima et al.T Kojima et al. 2016l. “CogKnife: Food Recognition from Their Cutting Sounds.” In 2016 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), , 1–6.

[13] Shin-ya Takahashi, Tsuyoshi Morimoto, Sakashi Maeda, Naoyuki TsurutaShin-ya Takahashi, Tsuyoshi Morimoto, Sakashi Maeda, Naoyuki Tsuruta 2003m. “Dialogue Experiment for Elderly People in Home Health Care System.” In International Conference on Text, Speech and Dialogue, eds. Václav Matoušek and Pavel Mautner. Berlin, Heidelberg: Springer Berlin Heidelberg, 418–23.

[14] Dan Istrate, Michel Vacher, Jean-François SerignatDan Istrate, Michel Vacher, Jean-François Serignat 2008n. “Embedded Implementation of Distress Situation Identification through Sound Analysis.” Journal on Information Technology in Healthcare (JITH) 6(3): 204–11.

[15] Richard E. Berg, David G. Stork, Brian HolmesRichard E. Berg, David G. Stork, Brian Holmes 1982o. “The Physics of Sound.” American Journal of Physics 50(10): 953–54.

[16] H.J. PainH.J. Pain 2005p. THE PHYSICS OF VIBRATIONS. 6th ed. John Wiley & Sons Ltd.

[17] “WAVE PCM Soundfile Format.”

[18] Todor Dimitrov GanchevTodor Dimitrov Ganchev 2005r. Wire Communications Laboratory Department of Computer and Electrical Engineering University of Patras Greece “Speaker Recognition.”

[19] Rashidul Hasan, Mustafa Jamil, Golam Rabbani, Saifur RahmanRashidul Hasan, Mustafa Jamil, Golam Rabbani, Saifur Rahman 2004s. “Speaker Identification Using Mel Frequency Cepstral Coefficients.” Proceedings of the 3rd International Conference on Electrical & Computer Engineering (ICECE 2004) (December): 28–30.

[20] Lindasalwa Muda, Mumtaj Begam, I. ElamvazuthiLindasalwa Muda, Mumtaj Begam, I. Elamvazuthi 2010t. “Voice Recognition Algorithms Using Mel Frequency Cepstral Coefficient (MFCC) and Dynamic Time Warping (DTW) Techniques.” 2(3): 138–43.

[21] Mandar Gilke, Pramod Kachare, Rohit Kothalikar, Varun Pius RodriguesMandar Gilke, Pramod Kachare, Rohit Kothalikar, Varun Pius Rodrigues 2012u. “MFCC-Based Vocal Emotion Recognition Using ANN.” 2012 International Conference on Electronics Engineering and Informatics (ICEEI 2012) 49(Iceei): 150–54.

[22] John C. Glover, Victor Lazzarini, Joseph TimoneyJohn C. Glover, Victor Lazzarini, Joseph Timoney 2011v. “Python for Audio Signal Processing.”

[23] Dongfang Wang, Shuangwei WangDongfang Wang, Shuangwei Wang 2016w. “The Research Progress about the Intelligent Recognition of Lung Sounds Normal Lung.” In 2016 2nd IEEE International Conference on Computer and Communications The, IEEE, 769–72.

[24] Y. Yamakawa, T. Shoji, K. Kakusho, M. MinohY. Yamakawa, T. Shoji, K. Kakusho, M. Minoh 2005x. Automatic Cooking Archiving with Spoken Dialogue with Assistant Agent.

[25] Inc HAPILABSInc HAPILABS “Hapifork.”

[26] Alejandro Ibarz et al.Alejandro Ibarz et al. 2008z. “Design and Evaluation of a Sound Based Water Flow Measurement System BT - Smart Sensing and Context.” In eds. Daniel Roggen et al. Berlin, Heidelberg: Springer Berlin Heidelberg, 41–54.

[27] M. Fezari, Bousbia-SalahM. Fezari, Bousbia-Salah 2007aa. “Speech and Sensor in Guiding an Electric Wheelchair.” M. Aut. Conrol Comp. Sci.

[28] O. Kumiko et al.O. Kumiko et al. 2004ab. Input Support for Elderly People Using Speech Recognition.

[29] J Wang, H Lee, J Wang, C LinJ Wang, H Lee, J Wang, C Lin 2008ac. “Robust Environmental Sound Recognition for Home Automation.” IEEE Transactions on Automation Science and Engineering 5(1): 25–31.

[30] T. GokhaleT. Gokhale 2017ad. “Machine Learning Based Identification of Pathological Heart Sounds.” Computing in Cardiology 43: 553–56.

[31] Rong PhoophuangpairojRong Phoophuangpairoj 2014ae. “Durian Ripeness Striking Sound Recognition Using N-Gram Models with N-Best Lists and Majority Voting.” In Recent Advances in Information and Communication Technology, eds. Sirapat Boonkrong, Herwig Unger, and Phayung Meesad. Cham: Springer International Publishing, 167–76.

[32] Medhanita Dewi Renanti, Agus Buono, Wisnu Ananta KusumaMedhanita Dewi Renanti, Agus Buono, Wisnu Ananta Kusuma 2013af. “Infant Cries Identification by Using Codebook as Feature Matching, and MFCC as Feature Extraction.” Journal of Theoretical and Applied Information Technology 56(3): 437–42.

[33] J G Wilpon, C N JacobsenJ G Wilpon, C N Jacobsen 1996ag. “A Study of Speech Recognition for Children and the Elderly.” In 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, , 349–52 vol. 1.

[34] A. Baba et al.A. Baba et al. 2004ah. “Acoustic Models of the Elderly for Large-Vocabulary Continuous Speech Recognition.” Electronics and Communications in Japan 87: 49–57.

[35] Michel Vacher et al.Michel Vacher et al. 2010ai. “Complete Sound and Speech Recognition System for Health Smart Homes: Application to the Recognition of Activities of Daily Living.” In New Developments in Biomedical Engineering, , 645–73.

Published

2019-05-24

How to Cite

Ranny, R., Suwardi, I. S., Rajab, T. L. E., & Lestari, D. P. (2019). Kajian Penelitian Pemrosesan Bunyi dan Aplikasinya pada Teknologi Informasi. JUITA: Jurnal Informatika, 7(1), 1–10. https://doi.org/10.30595/juita.v7i1.3491

Issue

Section

Articles

Similar Articles

> >> 

You may also start an advanced similarity search for this article.