SADDEL: Joint Speech Separation And Denoising Model Based On Multitask Learning

Abstract

Speech data collected in real-world scenarios often encounters two issues. First, multiple sources may exist simultaneously, and the number of sources may vary with time. Second, the existence of background noise in recording is inevitable. To handle the first issue, we refer to speech separation approaches, that separate speech from an unknown number of speakers. To address the second issue, we refer to speech denoising approaches, which remove noise components and retrieve pure speech signals. Numerous deep learning based methods for speech separation and denoising have been proposed that show promising results. However, few works attempt to address the issues simultaneously, despite speech separation and denoising tasks having similar nature. In this study, we propose a joint speech separation and denoising framework based on the multitask learning criterion to tackle the two issues simultaneously. The experimental results show that the proposed framework not only performs well on b

Stats

• citations0
• S2 citations—
• github stars0
• HF likes0
• heat score0.00
• arxiv keywu2020saddel

Related papers

• Audio-visual Speech Separation And Dereverberation With A Two-stage Multimodal Network (2019)12.47
• Jointly Detecting And Separating Singing Voice: A Multi-task Approach (2018)7.81
• Real-time Speech Enhancement And Separation With A Unified Deep Neural Network For Single/dual Talker Scenarios (2023)2.26
• A Multi-stage Triple-path Method For Speech Separation In Noisy And Reverberant Environments (2023)2.26
• Mad Twinnet: Masker-denoiser Architecture With Twin Networks For Monaural Sound Source Separation (2018)0.00
• Two-stage Model And Optimal SI-SNR For Monaural Multi-speaker Speech Separation In Noisy Environment (2020)0.00
• Preserving Background Sound In Noise-robust Voice Conversion Via Multi-task Learning (2022)0.00
• Masked Modeling Duo For Speech: Specializing General-purpose Audio Representation To Speech Using Denoising Distillation (2023)7.94