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Mutual Forcing: Dual-Mode Self-Evolution for Fast Autoregressive Audio-Video Character Generation WhisperPipe: A Resource-Efficient Streaming Architecture for Real-Time Automatic Speech Recognition Walking Through Uncertainty: An Empirical Study of Uncertainty Estimation for Audio-Aware Large Language Models PSP: An Interpretable Per-Dimension Accent Benchmark for Indic Text-to-Speech Praxy Voice: Voice-Prompt Recovery + BUPS for Commercial-Class Indic TTS from a Frozen Non-Indic Base at Zero Commercial-Training-Data Cost Korean aegyo speech shows systematic F1 increase to signal childlike qualities All That Glitters Is Not Audio: Rethinking Text Priors and Audio Reliance in Audio-Language Evaluation RAS: a Reliability Oriented Metric for Automatic Speech Recognition Speech Enhancement Based on Drifting Models HeadRouter: Dynamic Head-Weight Routing for Task-Adaptive Audio Token Pruning in Large Audio Language Models Hallo-Live: Real-Time Streaming Joint Audio-Video Avatar Generation with Asynchronous Dual-Stream and Human-Centric Preference Distillation Talker-T2AV: Joint Talking Audio-Video Generation with Autoregressive Diffusion Modeling Robust Audio-Text Retrieval via Cross-Modal Attention and Hybrid Loss Spectro-Temporal Modulation Representation Framework for Human-Imitated Speech Detection UniSonate: A Unified Model for Speech, Music, and Sound Effect Generation with Text Instructions Do LLM Decoders Listen Fairly? 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Zero-Shot Singing Synthesis With Structured Melody Control and Guidance RFM-Editing: Rectified Flow Matching for Text-guided Audio Editing CodecSep: Prompt-Driven Universal Sound Separation on Neural Audio Codec Latents DreamAudio: Customized Text-to-Audio Generation with Diffusion Models Computational Narrative Understanding for Expressive Text-to-Speech Gaussian Process Regression of Steering Vectors With Physics-Aware Deep Composite Kernels for Augmented Listening Towards Holistic Evaluation of Large Audio-Language Models: A Comprehensive Survey FMSD-TTS: Few-shot Multi-Speaker Multi-Dialect Text-to-Speech Synthesis for Ü-Tsang, Amdo and Kham Speech Dataset Generation Sat2Sound: A Unified Framework for Zero-Shot Soundscape Mapping Histogram-based Parameter-efficient Tuning for Passive and Active Sonar Classification Speculative End-Turn Detector for Efficient Speech Chatbot Assistant AudioX: A Unified Framework for Anything-to-Audio Generation Speech-FT: Merging Pre-trained And Fine-Tuned Speech Representation Models For Cross-Task Generalization Throat and acoustic paired speech dataset for deep learning-based speech enhancement Dementia classification from spontaneous speech using wrapper-based feature selection DASB - Discrete Audio and Speech Benchmark Basic syntax from speech: Spontaneous concatenation in unsupervised deep neural networks
FoVNet: Configurable Field-of-View Speech Enhancement with Low Computation and Distortion for Smart Glasses
Zhongweiyang Xu, Ali Aroudi, Ke Tan, Ashutosh Pandey, Jung-Suk L · 2024-08-13 · via cs.SD updates on arXiv.org

This paper presents a novel multi-channel speech enhancement approach, FoVNet, that enables highly efficient speech enhancement within a configurable field of view (FoV) of a smart-glasses user without needing specific target-talker(s) directions. It advances over prior works by enhancing all speakers within any given FoV, with a hybrid signal processing and deep learning approach designed with high computational efficiency. The neural network component is designed with ultra-low computation (about 50 MMACS). A multi-channel Wiener filter and a post-processing module are further used to improve perceptual quality. We evaluate our algorithm with a microphone array on smart glasses, providing a configurable, efficient solution for augmented hearing on energy-constrained devices. FoVNet excels in both computational efficiency and speech quality across multiple scenarios, making it a promising solution for smart glasses applications.

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