A Full Frequency Masking Vocoder for Legal Eavesdropping Conversation Recording

Neural Vocoder Feature Estimation for Dry Singing Voice Separation

Singing voice separation (SVS) is a task that separates singing voice audio from its mixture with instrumental audio. Previous SVS studies have mainly employed the spectrogram masking method which requires a large dimensionality in predicting the binary masks. In addition, they focused on extracting a vocal stem that retains the wet sound with the reverberation effect. This result may hinder the reusability of the isolated singing voice. This paper addresses the issues by predicting mel-spectrogram of dry singing voices from the mixed audio as neural vocoder features and synthesizing the singi…

LA-VocE: Low-SNR Audio-visual Speech Enhancement using Neural Vocoders

Audio-visual speech enhancement aims to extract clean speech from a noisy environment by leveraging not only the audio itself but also the target speaker's lip movements. This approach has been shown to yield improvements over audio-only speech enhancement, particularly for the removal of interfering speech. Despite recent advances in speech synthesis, most audio-visual approaches continue to use spectral mapping/masking to reproduce the clean audio, often resulting in visual backbones added to existing speech enhancement architectures. In this work, we propose LA-VocE, a new two-stage approac…

Advances in Speech Vocoding for Text-to-Speech with Continuous Parameters

Vocoders received renewed attention as main components in statistical parametric text-to-speech (TTS) synthesis and speech transformation systems. Even though there are vocoding techniques give almost accepted synthesized speech, their high computational complexity and irregular structures are still considered challenging concerns, which yield a variety of voice quality degradation. Therefore, this paper presents new techniques in a continuous vocoder, that is all features are continuous and presents a flexible speech synthesis system. First, a new continuous noise masking based on the phase d…

Self-Supervised Learning for Speech Enhancement through Synthesis

Modern speech enhancement (SE) networks typically implement noise suppression through time-frequency masking, latent representation masking, or discriminative signal prediction. In contrast, some recent works explore SE via generative speech synthesis, where the system's output is synthesized by a neural vocoder after an inherently lossy feature-denoising step. In this paper, we propose a denoising vocoder (DeVo) approach, where a vocoder accepts noisy representations and learns to directly synthesize clean speech. We leverage rich representations from self-supervised learning (SSL) speech mod…

基于音素的可控录音权限主动防窃听方法

Phoneme-Based Proactive Anti-Eavesdropping with Controlled Recording Privilege

针对现有超声波防窃听方案依赖能量掩蔽、易被去除且不支持授权录音的问题，提出基于音素的信息掩蔽噪声方法，优化传输策略并实现硬件原型，可将录音识别准确率降至50%以下且保留授权录音功能。