惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

云风的 BLOG
云风的 BLOG
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
博客园 - 叶小钗
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
V
V2EX
酷 壳 – CoolShell
酷 壳 – CoolShell
月光博客
月光博客
人人都是产品经理
人人都是产品经理
宝玉的分享
宝玉的分享
博客园 - 司徒正美
WordPress大学
WordPress大学
Microsoft Azure Blog
Microsoft Azure Blog
罗磊的独立博客
Vercel News
Vercel News
T
The Blog of Author Tim Ferriss
T
Tailwind CSS Blog
A
About on SuperTechFans
Apple Machine Learning Research
Apple Machine Learning Research
L
LangChain Blog
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
V
Visual Studio Blog
S
SegmentFault 最新的问题
Google DeepMind News
Google DeepMind News
博客园 - 聂微东

cs.SD updates on arXiv.org

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? Benchmarking How Language Model Priors Shape Bias in Speech Recognition Materialistic RIR: Material Conditioned Realistic RIR Generation SpeechParaling-Bench: A Comprehensive Benchmark for Paralinguistic-Aware Speech Generation ONOTE: Benchmarking Omnimodal Notation Processing for Expert-level Music Intelligence From Image to Music Language: A Two-Stage Structure Decoding Approach for Complex Polyphonic OMR ATIR: Towards Audio-Text Interleaved Contextual Retrieval Enhancing Speaker Verification with Whispered Speech via Post-Processing Environmental Sound Deepfake Detection Using Deep-Learning Framework Towards Streaming Target Speaker Extraction via Chunk-wise Interleaved Splicing of Autoregressive Language Model BEAT: Tokenizing and Generating Symbolic Music by Uniform Temporal Steps Deep Supervised Contrastive Learning of Pitch Contours for Robust Pitch Accent Classification in Seoul Korean HalluAudio: A Comprehensive Benchmark for Hallucination Detection in Large Audio-Language Models UAF: A Unified Audio Front-end LLM for Full-Duplex Speech Interaction Voice of India: A Large-Scale Benchmark for Real-World Speech Recognition in India Tadabur: A Large-Scale Quran Audio Dataset
Reproducing the Acoustic Velocity Vectors in a Circular L...
Jiarui Wang, Thushara Abhayapala, Jihui Aimee Zhang, Prasanga Sa · 2024-03-19 · via cs.SD updates on arXiv.org

Acoustic velocity vectors are important for human's localization of sound at low frequencies. This paper proposes a sound field reproduction algorithm, which matches the acoustic velocity vectors in a circular listening area. In previous work, acoustic velocity vectors are matched either at sweet spots or on the boundary of the listening area. Methods based on sweet spots experience performance degradation when the listener moves away from sweet spots, whereas measuring the acoustic velocity vectors on the boundary requires complicated measurement setup. This paper proposes the radial independent cylindrical harmonic coefficients of the acoustic velocity vectors (CHV-indR coefficients) in the circular listening area, which are calculated from the cylindrical harmonic coefficients of the pressure in the circular listening area by using the sound field translation formula. The cylindrical harmonic coefficients of the pressure can be measured by a circular microphone array, which can be bought off-the-shelf. By matching the CHV-indR coefficients, the acoustic velocity vectors are reproduced throughout the listening area. Simulations show that at low frequencies, where the acoustic velocity vectors are the dominant factor for localization, the proposed reproduction method based on matching the CHV-indR coefficients results in higher accuracy in reproduced acoustic velocity vectors when compared with traditional method based on matching the cylindrical harmonic coefficients of the pressure.