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Complex nested U-Net-based speech enhancement model using a dual-branch decoder (이중 분기 디코더를 사용하는 복소 중첩 U-Net 기반 음성 향상 모델)

  • Seorim Hwang;Sung Wook Park;Youngcheol Park
    • The Journal of the Acoustical Society of Korea
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    • v.43 no.2
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    • pp.253-259
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    • 2024

  • This paper proposes a new speech enhancement model based on a complex nested U-Net with a dual-branch decoder. The proposed model consists of a complex nested U-Net to simultaneously estimate the magnitude and phase components of the speech signal, and the decoder has a dual-branch decoder structure that performs spectral mapping and time-frequency masking in each branch. At this time, compared to the single-branch decoder structure, the dual-branch decoder structure allows noise to be effectively removed while minimizing the loss of speech information. The experiment was conducted on the VoiceBank + DEMAND database, commonly used for speech enhancement model training, and was evaluated through various objective evaluation metrics. As a result of the experiment, the complex nested U-Net-based speech enhancement model using a dual-branch decoder increased the Perceptual Evaluation of Speech Quality (PESQ) score by about 0.13 compared to the baseline, and showed a higher objective evaluation score than recently proposed speech enhancement models.

  • https://doi.org/10.7776/ASK.2024.43.2.253 인용 PDF