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.
Get the few papers worth your time in Sound every morning.
Follow Sound and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 4
The Voice on the Line
A transcriber listening through one microphone also hears everyone near it.Geometric Consistency Based Label-Free Validation for Checkpoint Selection in Audio Active Learning
Audio active learning (AL) trains a classifier at low annotation cost by labeling only an informative fraction of an unlabeled collection over successive rounds.Should Pseudo-Labels Share Mini-Batches with Labeled Examples? Semi-Supervised Continual Active Learning with Limited Training Cost
Active learning (AL) reduces annotation by querying informative examples.Integrate the Reward, Don't Sample It: Window Likelihood for Interruptions and Backchannels in Full-Duplex Speech Models
A full-duplex spoken dialogue model must yield when the user cuts in and hold when the user merely backchannels.Multimodal Concert Video Editing: System Design and Exploratory Evaluation
Editing multi-camera concerts requires coordinated decisions about musical relevance, visual quality and cut timing.ConformalMOS: Uncertainty-Aware MOS Prediction with Conformal Intervals and Ordinal Modeling
Accurate prediction of human Mean Opinion Scores (MOS) is crucial for evaluating synthetic speech quality in text-to-speech (TTS) and voice conversion (VC).EmoNet: A Lightweight Attention-Based CNN for Speech Emotion Recognition
Speech Emotion Recognition (SER) is a fundamental task in affective computing that enables applications such as mental health assessment, human-computer interaction, and automated customer support…AudioFM: Towards General Purpose Audio Representation Learning
Learning audio representations that effectively bridge holistic global soundscapes with fine-grained acoustic moments is a long-standing goal in self-supervised learning.Does Notation Matter? MusicXML Tokenisation for Symbolic Music Generation and Understanding
Symbolic music representations encode musical content at varying levels of completeness, from performance-oriented formats such as MIDI to fully notated scores such as MusicXML.In-Context Adapter Generation for Compositional Generalization in Large Audio Language Models
Large audio language models (LALMs) have achieved strong performance on standard speech and audio understanding tasks, yet their ability to systematically generalize to novel task compositions…Spatial Audio Generation and Editing with Executable Plans and Self-Distilling Transfusion
Spatial audio authoring coordinates source decisions with soundfield synthesis.Finite-Sample Sensitivity of Kernel Metrics for Generative Evaluation
Kernel distances such as the Kernel Inception Distance (KID) and the Kernel Audio Distance (KAD) compare generated and reference samples in an embedding space, and model comparisons rest on their…Audio-R1: Audio Reasoning through Reinforcement Learning on Self-Supervised Tasks
Reasoning is increasingly important for large audio-language models (LALMs), yet remains relatively underexplored compared with text-only and vision-language models.MI-MIDI 2: From Observation to Control with Sparse Autoencoders in Text-to-MIDI Generation
Sparse autoencoders (SAEs) can expose features of a generative model without predefined labels, but in language models the evidence used to interpret these features has proven an unreliable guide to…DIAL-S2ST: Learning Latency Control for Simultaneous Speech-to-Speech Translation
We propose DIAL-S2ST, a post-training method for learning inference-time latency control in simultaneous speech-to-speech translation models.Supervised Source Separation of Electric Vehicle Interior Noise Using a Hybrid Transformer Architecture
The interior sound of an electric vehicle is a superposition of several distinct noise contributions - wind noise, tire noise, powertrain (electric drive unit and inverter) noise, and…ChoreoStudio: Planning What, When, and Who in Music-Driven Group Choreography
Music-driven group dance generation must decide not only how each dancer moves, but also what formation the group should form, when it should change, and who should execute each transition.Why Full-Duplex Speech Models Collapse in Long Conversations
Full-duplex speech models listen and speak at the same time, which makes them promising for natural, open-ended conversation.MusicTwins: Training Audio-Language Models to Listen like Their Persona
People differ in how they perceive music, what associations they make with it, what they like about it, and how they respond to it.Interpretable Singing Emotion Recognition Using Acoustic and Vocal Technique Features
Singing emotion recognition relies predominantly on deep learning models that achieve strong performance but offer limited insight into the vocal characteristics driving emotion, of- ten overlooking…