Applied & Human-Centered · Computer Science & AI
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The newest papers in Sound that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
553 papers, from 4 September 2026 to 5 November 2026: 553 arXiv preprints.
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Newest papers, page 28
Frequency Estimation Based on SNR-adaptive Frequency Estimator Under Wide SNR Range
Frequency estimation is the problem of estimating individual tone frequencies from noisy multi-tone sinusoidal signals.Comparing Self-Supervised and Domain-Invariant Features for Cross-Domain Voice Phishing Detection
Voice phishing detection faces three critical challenges: real criminal recordings are unavailable due to privacy constraints; when available, only a handful of samples exist, insufficient for…KABURI-TTS: Phoneme-Keyed Activity-conditioned Bi-channel Utterance Rendering for Interaction
Realizing full-duplex spoken dialogue requires large amounts of two-channel, one-speaker-per-channel conversational speech data.Iterative Audio Separation with Mixture Consistency via MIMO Model Extension
This paper proposes a general framework for stable and effective iterative audio separation with mixture consistency by extending source separation models to a multi-input multi-output (MIMO)…TAD: Token-Adaptive Contrastive Decoding with Confidence-Guided Gating for Hallucination Mitigation in Large Audio-Language Models
Large audio-language models (LALMs) can hallucinate audio objects, answering "yes" to absent sound events, thus undermining reliability in audio question answering.RAFM-SER++: A Lightweight Multimodal Emotion Recognition Framework for Real-Time Behavioral Monitoring in Surveillance Systems
Recent multimodal Speech Emotion Recognition (SER) systems achieve high accuracy through interaction-heavy cross-modal transformers, but their computational cost limits deployment in…Clean Accuracy Does Not Guarantee Provenance Robustness: A Prospective Codec-Stress Evaluation of Audio Attribution
Audio provenance attribution - which system produced a synthetic utterance - is reported at near-ceiling accuracy on clean benchmarks, yet audio reaching an analyst has usually been transcoded.When Speech Meets Lips: Interpretable Audio-Visual Synchronization for L2 Pronunciation Assessment
Automatic Pronunciation Assessment (APA) systems have achieved strong performance with transformer-based models and self-supervised speech representations.BinauralVAE: Spatial Audio Reconstruction For World Models
Embodied artificial intelligence has historically very much relied on visual perception, leading to a proliferation of multiple vision-centric world models.Where Does the Sound Go? Tracing Acoustic Information Loss in Audio-Conditioned LLMs
Audio-conditioned language models often underuse acoustic cues such as prosody, emotion, and non-speech sounds, raising the question of whether ASR-supervised frontends discard this information…Tri-PvP: Exposing Modality Bias in Omni-Modal Large Language Models through Perceptual-Propositional Evidence Conflicts
Omni-modal large language models (OLLMs) jointly process vision, audio, and text, yet their modality bias under cross-modal conflict remains underexplored.TamilEOT: A Dataset and Model for Semantic End-of-Turn Detection in Tamil Telephone Speech
A voice agent has to decide, at every pause, whether the user has finished speaking.Emotion as a Distribution: Joint Valence-Arousal Probability Learning for Speaker-Independent Multimodal Emotion Recognition
Human emotion is graded and frequently mixed, yet most multimodal recognizers collapse it onto a single hard label.