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All Journal International Journal of Electrical and Computer Engineering TEKNIK INFORMATIKA TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmu Komputer dan Agri-Informatika Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Ilmiah FIFO Jurnal Sistem Informasi
Shofi, Imam Marzuki
Universitas Islam Negeri Syarif Hidayatullah Jakarta
Agriculture, Biological Sciences & Forestry Computer Science & IT Electrical & Electronics Engineering

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Impact of Wavelet Denoising on LSTM-Based Greeting Sentence Recognition Using the IndSpeech Teldialog SVCR Dataset Shabira Zhillan; Wardhani, Luh Kesuma; Anggraini, Nenny; Nashrul Hakiem; Imam Marzuki Shofi
JURNAL TEKNIK INFORMATIKA Vol. 19 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v19i1.49040

Abstract

Speech signals play a crucial role in human communication, particularly in speech recognition systems. However, speech recognition performance is often compromised by noise in the audio signal. This study aims to examine the effect of wavelet denoising technique on greeting sentence data containing artificial white noise before performing speech recognition using Long Short-Term Memory (LSTM). Mel Frequency Cepstral Coefficient (MFCC) is used as speech feature extraction. The results show that speech recognition accuracy reaches 90% on clean data. Accuracy drops to 51% when tested on data with noise, indicating a significant decrease of 39 percentage points. After applying the wavelet denoising method, accuracy improved using the two best parameter combinations. The combination with the highest SNR value resulted in an improvement of 18 percentage points, while the combination with the highest PESQ value resulted in an improvement of 13 percentage points. These findings indicate that the wavelet denoising method is capable of improving the performance of LSTM-based speech recognition in noisy environments.
Co-Authors Ahmad Arya Swaraja Ahmad Nurul Fajar Anif Hanifa Setianingrum Anif Hanifa Setyaningrum Aryajaya Alamsyah Dea Herwinda Kalokasari Fajar Nugraha Wahyu Fenty Eka Muzayyana Agustin Fikriansyah Martunus Hendra Bayu Suseno Luh Kesuma Wardhani Nashrul Hakiem Nashrul Hakiem Nenny Anggraini Nenny Anggraini, Nenny Prihatini, Rahayu Suci Qurrotul Aini Rahayu Suci Prihatini Setyaningrum, Anif Hanifa Shabira Zhillan Siti Ummi Masruroh Yudi Setiadi