Dual-Stage Low-Complexity Reconfigurable Speech Enhancement
This paper proposes a dual-stage, low complexity, and reconfigurable technique to enhance the speech contaminated by various types of noise sources. Driven by input data and audio contents, the proposed dual-stage speech enhancement approach performs a coarse and fine processing in the first-stage and second-stage, respectively. In this paper, we demonstrate that the proposed speech enhancement solution significantly enhances the metrics of 3-fold QUality Evaluation of Speech in Telecommunication (3QUEST) consisting of speech mean-opinion-score (SMOS) and noise MOS (NMOS) for near-field and far-field applications. Moreover, the proposed speech enhancement approach greatly improves both the signal-to-noise ratio (SNR) and subjective listening experience. For comparisons, the traditional speech enhancement methods reduce the SMOS although they increase NMOS and SNR. In addition, the proposed speech enhancement scheme can be easily adopted in both capture path and speech render path for speech communication and conferencing systems, and voice-trigger applications.
Code (0)
등록된 구현이 없습니다.
Tasks
Speech EnhancementSimilar Papers 제목 키워드 기반
A Dual-Staged Context Aggregation Method Towards Efficient End-To-End Speech Enhancement
In speech enhancement, an end-to-end deep neural network converts a noisy speech signal to a clean speech directly in time domain without time-frequency transformation or mask estimation. However, aggregating contextual …
Speech EnhancementTS-URGENet: A Three-stage Universal Robust and Generalizable Speech Enhancement Network
Universal speech enhancement aims to handle input speech with different distortions and input formats. To tackle this challenge, we present TS-URGENet, a Three-Stage Universal, Robust, and Generalizable speech Enhancemen…
Speech EnhancementImproving GANs for Speech Enhancement
Generative adversarial networks (GAN) have recently been shown to be efficient for speech enhancement. However, most, if not all, existing speech enhancement GANs (SEGAN) make use of a single generator to perform one-sta…
Speech EnhancementFB-MSTCN: A Full-Band Single-Channel Speech Enhancement Method Based on Multi-Scale Temporal Convolutional Network
In recent years, deep learning-based approaches have significantly improved the performance of single-channel speech enhancement. However, due to the limitation of training data and computational complexity, real-time en…
DenoisingSpeech DenoisingSpeech EnhancementPLDNet: PLD-Guided Lightweight Deep Network Boosted by Efficient Attention for Handheld Dual-Microphone Speech Enhancement
Low-complexity speech enhancement on mobile phones is crucial in the era of 5G. Thus, focusing on handheld mobile phone communication scenario, based on power level difference (PLD) algorithm and lightweight U-Net, we pr…
Speech Enhancement