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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
Frequency domain variant of Velvet noise and its applicat...
Hideki Kawahara, Ken-Ichi Sakakibara, Mitsunori Mizumachi, Hidek · 2019-09-10 · via cs.SD updates on arXiv.org

We propose a new family of test signals for acoustic measurements such as impulse response, nonlinearity, and the effects of background noise. The proposed family complements difficulties in existing families, the Swept-Sine (SS), pseudo-random noise such as the maximum length sequence (MLS). The proposed family uses the frequency domain variant of the Velvet noise (FVN) as its building block. An FVN is an impulse response of an all-pass filter and yields the unit impulse when convolved with the time-reversed version of itself. In this respect, FVN is a member of the time-stretched pulse (TSP) in the broadest sense. The high degree of freedom in designing an FVN opens a vast range of applications in acoustic measurement. We introduce the following applications and their specific procedures, among other possibilities. They are as follows. a) Spectrum shaping adaptive to background noise. b) Simultaneous measurement of impulse responses of multiple acoustic paths. d) Simultaneous measurement of linear and nonlinear components of an acoustic path. e) Automatic procedure for time axis alignment of the source and the receiver when they are using independent clocks in acoustic impulse response measurement. We implemented a reference measurement tool equipped with all these procedures. The MATLAB source code and related materials are open-sourced and placed in a GitHub repository.