Dampak Low-pass Filter pada Identifikasi Suara Manusia (The Impact of Low-Pass Filter in Speaker Identification)

AHMAD RIZKY PRAYOGI

Informasi Dasar

20.04.1044
006.3
Karya Ilmiah - Skripsi (S1) - Reference

Speaker identification model commonly uses Mel Frequency Ceptral Coefficient (MFCC) and Gaussian Mixture Model (GMM). Due to many weaknesses from previous studies for noised speech, here a low-pass-filter is proposed to reduce the high-frequency signals. The low-pass-filter is expected to calculate cut-offs. Experimental results show that the low-pass filter significantly improves the accuracy of sound detection for the high noised signal.

Subjek

ARTIFICIAL INTELLIGENCE
 

Katalog

Dampak Low-pass Filter pada Identifikasi Suara Manusia (The Impact of Low-Pass Filter in Speaker Identification)
 
 
Indonesia

Sirkulasi

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Pengarang

AHMAD RIZKY PRAYOGI
Perorangan
SUYANTO
 

Penerbit

Universitas Telkom, S1 Informatika
Bandung
2020

Koleksi

Kompetensi

  • CCH3F3 - KECERDASAN BUATAN
  • CSG3G3 - KECERDASAN MESIN DAN ARTIFISIAL
  • CCH4A3 - PENULISAN PROPOSAL
  • CIG4B3 - SOFT COMPUTING
  • CCH4D4 - TUGAS AKHIR
  • CII4A2 - PENULISAN PROPOSAL
  • CII4E4 - TUGAS AKHIR
  • CPI4A2 - PENULISAN PROPOSAL
  • III4A4 - TUGAS AKHIR
  • CII9G6 - PROPOSAL PENELITIAN

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