Journals / Electronic Letters on Science and Engineering / 2007 / Cilt: 3 - Sayı: 1

Speaker Recognition Using Mel-Frequency Cepstrum Coefficients and Artificial Neural Network for Security Systems

Güvenlik Sistemleri Için Mel Frekans Kepstrum Katsayilari ve Yapay Sinir Aglari Kullanilarak Konusmaci Tanima

Pages
8–15
Publication Date
2007-04-01
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Study is based on three steps; In first step analog sound that taken is converted to data to be processed and determine own characteristic of each sound. in second step converted sounds called data are used to train neural network. at last step trained neural network is test by the test sounds and obtained istatistical informations.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study; the sample sounds of the speakers are transfered to computer for identifing the speaker.
📊
Key Findings & Data:In this study; the sample sounds of the speakers are transfered to computer for identifing the speaker.
💡
Conclusion & Impact:Study is based on three steps; In first step analog sound that taken is converted to data to be processed and determine own characteristic of each sound. in second step converted sounds called data are used to train neural network. at last step trained neural network is test by the test sounds and obtained istatistical informations.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Sinir Aglari · Konusmaci kimliklendirme · Konusmaci tanima

Abstract

In this study; the sample sounds of the speakers are transfered to computer for identifing the speaker. Study is based on three steps; In first step analog sound that taken is converted to data to be processed and determine own characteristic of each sound. in second step converted sounds called data are used to train neural network. at last step trained neural network is test by the test sounds and obtained istatistical informations.

Özet

Bu çalismada konusmaci ses örnekleri bilgisayara alinarak bu konusmacilarin kimliklerinin belirlenmesi saglanmistir. Çalisma üç asamadan olusmaktadir. Ilk asama konusmaci sesinin dijital ortamda veriye dönüstürülmesi islenebilir hale getirilerek özellik çikartilmasi ikinci asama elimizdeki konusmaci ses örnekleriyle yapay sinir aginin egitilmesi ve son asama da egitilmis sinir agina test verileri göndererek istatistik bilgiler elde edilmesidir.

🔖

Cite This Article

KÜÇÜKER, A., YÜZKOLLAR, C., SANSLİ, A., SEN, F. (2007). Speaker Recognition Using Mel-Frequency Cepstrum Coefficients and Artificial Neural Network for Security Systems. Electronic Letters on Science and Engineering, Cilt: 3 - Sayı: 1, 8–15. https://ajindex.com/articles/133694

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...