PURWARUPA SISTEM PENYAKLARAN ALAT ELEKTRONIK BERBASIS PENGENALAN UCAPAN MENGGUNAKAN RASPBERRY PI
Switch system using button on electronic appliances is less efficient for some people who have physical limitations. Humans could control the switching system of electronic appliances easier using their speech by utilizing the speech recognition. In this research, speech recognition system receives...
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| Format: | Thesis |
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[Yogyakarta] : Universitas Gadjah Mada
2013
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| Subjects: |
| _version_ | 1797033977156993024 |
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| author | , AHMAD ANUNG PROBO KUNCORO , Prof. Dr. Jazi Eko Istiyanto, M.Sc. |
| author_facet | , AHMAD ANUNG PROBO KUNCORO , Prof. Dr. Jazi Eko Istiyanto, M.Sc. |
| author_sort | , AHMAD ANUNG PROBO KUNCORO |
| collection | UGM |
| description | Switch system using button on electronic appliances is less efficient for some people who have physical limitations. Humans could control the switching system of electronic appliances easier using their speech by utilizing the speech recognition.
In this research, speech recognition system receives human speech input through the microphone and then the speech processed by Raspberry Pi which also control the switching system. Speech recognition is built using Hidden Markov Model covered in Hidden Markov Model Toolkit (HTK) and run by Julius software. Instruction that will be recognized are clustered in a grammar and added with a transcription of the word to be trained as an acoustic model. Speech recognition method use the acoustic model to be compared with speech signal. The output of speech recognition is then used as an instruction in electronics switching system. Speech recognition using English language with American English dialect that refers from VoxForge dictionary.
The result of this research is a prototype of speech recognition system as a switching system control using Raspberry Pi as processing unit using microphone from Logitech C920 webcam. The system trial is done by testing the effect of voice signal gain and speech recognition test in environment condition with noise level of 20-30 dB. The best result is achieved when the gain is 30-40 dB. The success rate of speech recognition using processing unit Raspberry Pi is 83,50%. This system can control the switching of electronic appliances based on human speech input using Raspberry Pi. |
| first_indexed | 2024-03-13T23:03:37Z |
| format | Thesis |
| id | oai:generic.eprints.org:123461 |
| institution | Universiti Gadjah Mada |
| last_indexed | 2024-03-13T23:03:37Z |
| publishDate | 2013 |
| publisher | [Yogyakarta] : Universitas Gadjah Mada |
| record_format | dspace |
| spelling | oai:generic.eprints.org:1234612016-03-04T08:21:30Z https://repository.ugm.ac.id/123461/ PURWARUPA SISTEM PENYAKLARAN ALAT ELEKTRONIK BERBASIS PENGENALAN UCAPAN MENGGUNAKAN RASPBERRY PI , AHMAD ANUNG PROBO KUNCORO , Prof. Dr. Jazi Eko Istiyanto, M.Sc. ETD Switch system using button on electronic appliances is less efficient for some people who have physical limitations. Humans could control the switching system of electronic appliances easier using their speech by utilizing the speech recognition. In this research, speech recognition system receives human speech input through the microphone and then the speech processed by Raspberry Pi which also control the switching system. Speech recognition is built using Hidden Markov Model covered in Hidden Markov Model Toolkit (HTK) and run by Julius software. Instruction that will be recognized are clustered in a grammar and added with a transcription of the word to be trained as an acoustic model. Speech recognition method use the acoustic model to be compared with speech signal. The output of speech recognition is then used as an instruction in electronics switching system. Speech recognition using English language with American English dialect that refers from VoxForge dictionary. The result of this research is a prototype of speech recognition system as a switching system control using Raspberry Pi as processing unit using microphone from Logitech C920 webcam. The system trial is done by testing the effect of voice signal gain and speech recognition test in environment condition with noise level of 20-30 dB. The best result is achieved when the gain is 30-40 dB. The success rate of speech recognition using processing unit Raspberry Pi is 83,50%. This system can control the switching of electronic appliances based on human speech input using Raspberry Pi. [Yogyakarta] : Universitas Gadjah Mada 2013 Thesis NonPeerReviewed , AHMAD ANUNG PROBO KUNCORO and , Prof. Dr. Jazi Eko Istiyanto, M.Sc. (2013) PURWARUPA SISTEM PENYAKLARAN ALAT ELEKTRONIK BERBASIS PENGENALAN UCAPAN MENGGUNAKAN RASPBERRY PI. UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=63572 |
| spellingShingle | ETD , AHMAD ANUNG PROBO KUNCORO , Prof. Dr. Jazi Eko Istiyanto, M.Sc. PURWARUPA SISTEM PENYAKLARAN ALAT ELEKTRONIK BERBASIS PENGENALAN UCAPAN MENGGUNAKAN RASPBERRY PI |
| title | PURWARUPA SISTEM PENYAKLARAN ALAT ELEKTRONIK BERBASIS PENGENALAN UCAPAN MENGGUNAKAN RASPBERRY PI |
| title_full | PURWARUPA SISTEM PENYAKLARAN ALAT ELEKTRONIK BERBASIS PENGENALAN UCAPAN MENGGUNAKAN RASPBERRY PI |
| title_fullStr | PURWARUPA SISTEM PENYAKLARAN ALAT ELEKTRONIK BERBASIS PENGENALAN UCAPAN MENGGUNAKAN RASPBERRY PI |
| title_full_unstemmed | PURWARUPA SISTEM PENYAKLARAN ALAT ELEKTRONIK BERBASIS PENGENALAN UCAPAN MENGGUNAKAN RASPBERRY PI |
| title_short | PURWARUPA SISTEM PENYAKLARAN ALAT ELEKTRONIK BERBASIS PENGENALAN UCAPAN MENGGUNAKAN RASPBERRY PI |
| title_sort | purwarupa sistem penyaklaran alat elektronik berbasis pengenalan ucapan menggunakan raspberry pi |
| topic | ETD |
| work_keys_str_mv | AT ahmadanungprobokuncoro purwarupasistempenyaklaranalatelektronikberbasispengenalanucapanmenggunakanraspberrypi AT profdrjaziekoistiyantomsc purwarupasistempenyaklaranalatelektronikberbasispengenalanucapanmenggunakanraspberrypi |