Applied & Human-Centered · Computer Science & AI
Sound
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 8
SynerGest: Temporal-Spatial Synergistic Gesture Generation for Dyadic Conversations
Co-speech gesture generation in dyadic conversations for creating immersive virtual avatars remains highly challenging.From Spectrograms to Shallow Speech SSL: Audio-Frontend Design for Generator-Disjoint and Low-Latency Audio--Visual Deepfake Detection
Video-mediated conversational systems rely on synchronized speech and facial video, making audio--visual input integrity important for reliable perception.CoSTA: Compressed Speech Token Adaptation for Efficient Spoken Dialogue Models
Spoken Dialogue Models (SDMs) typically share a speech-token space for generation and synthesis, leading to long autoregressive sequences and costly inference.Full-Duplex Interaction with Speech, Expressions and Gestures
Human face-to-face conversation requires coordinating speech, gestures and expressions across both speaking and listening.DuET: Note-Frame Dual Encoding for Piano Performance-to-Score Transcription
Transcribing expressive piano performances into scores requires interpreting individual note timings within an underlying metrical structure.Hear, Localize, and Reason: Spatially Aware Scene Understanding for Audio-Visual LLMs
Audio-visual large language models (AV-LLMs) have made strong progress in multimodal understanding, yet most treat audio as monaural semantic content, limiting their ability to reason about where…Qwen-Audio-Jev: A Unified Interface for Audio Decisions
Large audio language models (LALMs) have made substantial progress in audio understanding.Bias Mitigation in Audio-Enabled LLMs through Adversarial Training and Distillation Methods
Audio-enabled large language models (AuLLMs) allow users to interact with them simply by talking to them, without the need for an intermediate transcription.CF-AVSS: A Coarse-to-Fine Audio-Visual Speech Separation Framework with Target-Speaker Refinement and Post-Fusion for Real-World AVSE Challenge
Audio-visual speech enhancement (AVSE) leverages visual cues to recover target speech from mixtures corrupted by reverberation, noise, and overlapping speakers.How Much Physics Can Vision Learn from Audio? Probing and Distilling Damping Structure
Physical understanding is crucial for decision making, yet vision models struggle to infer properties such as damping that govern how materials behave.Backward Compatibility in Zero-Bit Neural Audio Watermarking
Neural watermarking systems are typically trained as tightly coupled embedder-detector pairs and implicitly assume static deployment.Disentangling Depression from Cognitive Decline in Elderly Speech Using Concurrent Clinical Assessments
Detecting depression from speech in elderly patients with mild cognitive impairment (MCI) is complicated by overlapping acoustic effects of cognitive decline.PW-Pruning: Phase-Aware Expert Selection for Speech-Centric Omni-Modal Models
Sparse routing reduces per-token computation but leaves the full expert bank resident in memory.ELARSpeech: A 30K-Hour Dataset Across 675 Underrepresented Languages for Long-Tail Multilingual Speech Technologies
Massively multilingual speech modeling has made remarkable progress in recent years, yet existing training resources and benchmarks still underrepresent much of the linguistic long tail.What Does LALM Post-training Learn? Rethinking Audio Understanding and Reasoning Capabilities
Post-training often improves the performance of large audio-language models on audio understanding and reasoning benchmarks.ONCship: A Large-Scale Underwater Acoustic Corpus for Ship Recognition
Recent advances in deep learning have significantly improved underwater acoustic vessel recognition.SEA-HELM Audio: Evaluating Multilingual ASR-LLM Pipeline Performance Across SEA-HELM Subsets
We introduce SEA-HELM Audio, a Southeast Asian (SEA) multilingual evaluation framework that extends the text-based SEA-HELM benchmark to assess performance degradation in cascaded automatic speech…Few-Shot Adaptation for Anomalous Sound Detection at Low False-Positive Rate
Reliable fault detection is crucial for industrial machinery in large-scale facilities, where unexpected failures can cause costly downtime and production interruptions.ACR-Net: Mitigating Semantic Dominance via Contrastive Acoustic-Semantic Decoupling
Speech Emotion Recognition (SER) models and Audio LLMs fail when vocal tone contradicts textual semantics.MultiPartyTurnBench: Benchmarking Floor Control in Multi-Party Spoken Dialogue
Full-duplex speech systems must decide when to enter, hold, or relinquish the conversational floor, even as multiple speakers overlap or backchannel without taking it.