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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
An accurate measurement of parametric array using a spuri...
Woongji Kim, Beomseok Oh, Junsuk Rho, Wonkyu Moon · 2025-04-17 · via cs.SD updates on arXiv.org

Parametric arrays (PA) offer exceptional directivity and compactness compared to conventional loudspeakers, facilitating various acoustic applications. However, accurate measurement of audio signals generated by PA remains challenging due to spurious ultrasonic sounds arising from microphone nonlinearities. Existing filtering methods, including Helmholtz resonators, phononic crystals, polymer films, and grazing incidence techniques, exhibit practical constraints such as size limitations, fabrication complexity, or insufficient attenuation. To address these issues, we propose and demonstrate a novel acoustic filter based on the design of a half-wavelength resonator. The developed filter exploits the nodal plane in acoustic pressure distribution, effectively minimizing microphone exposure to targeted ultrasonic frequencies. Fabrication via stereolithography (SLA) 3D printing ensures high dimensional accuracy, which is crucial for high-frequency acoustic filters. Finite element method (FEM) simulations guided filter optimization for suppression frequencies at 40 kHz and 60 kHz, achieving high transmission loss (TL) around 60 dB. Experimental validations confirm the filter's superior performance in significantly reducing spurious acoustic signals, as reflected in frequency response, beam pattern, and propagation curve measurements. The proposed filter ensures stable and precise acoustic characterization, independent of measurement distances and incidence angles. This new approach not only improves measurement accuracy but also enhances reliability and reproducibility in parametric array research and development.