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 25
Typhoon ASR Streaming: Steerable Low-Latency Thai Speech Recognition with Real-Time Shallow Fusion
Open Thai automatic speech recognition (ASR) is dominated by offline, Whisper-based models that read the whole utterance before transcribing, ruling out low-latency uses such as live captioning and…Rethinking Procedural Audio Pre-training: Source Scaling and Objective Adaptation
Procedural audio has emerged as a viable source for transferable audio representation learning, but its design principles remain unclear.We revisit two questions: how a procedural source should be…Augmenting Large Audio-Language Models with Frame-Level Grounding for Fine-Grained Temporal Perception
Large Audio-Language Models (LALMs) have substantially advanced general audio understanding, yet they remain limited in fine-grained temporal perception, particularly in precise event localization.MAST: Label-Efficient, Robust, and Generalizable Sound Detection for Biodiversity Monitoring via Masked Audio Pretraining and Self-Training
Passive acoustic monitoring can measure biodiversity at larger scales, but time--frequency annotation of animal vocalizations is expensive, site-specific, and difficult to sustain at scale.BioDCASE: Active Learning for Bioacoustics
Ecological monitoring increasingly relies on machine learning models, whose performance depends on the quality and quantity of labelled data.Reducing the Output-Mode Gap in Speech Language Models via Joint-Output On-Policy Distillation
Autoregressive generation of interleaved text and acoustic tokens is a common approach to spoken-response generation in speech large language models.MUUNRiver-Bench: Diagnosing Relation-Dependent Music Retrieval with Multimodal Instructions
Music retrieval is relation-dependent: given a reference track, a listener may seek its style with a new theme, a cover, or a comparable voice, and these intents demand contradictory rankings.Timbre Analysis of the Hulusi, a Southwestern Chinese Free-Reed Instrument, using Machine Learning
The hulusi is a wind instrument that was invented in Yunnan Province, China, and has become tremendously popular in recent years.AURA: Unified Multimodal Framework for Conversational Music Editing
Instruction-guided music editors typically process each request independently, limiting their ability to support workflows in which users progressively refine a track.Bridging the Modality Gap in Long-Form Clinical Audio: A Comparative Study of Lightweight and Heavyweight End-to-End SOAP Generation
Automating clinical documentation from long-form doctor-patient conversations remains challenging for modern audio-language models.Neyshekar: An Open Persian Read-Speech Corpus for Automatic Speech Recognition
Neyshekar is presented as an open Persian read-speech corpus designed for coverage of both formal and informal language, named entities, and longer utterances.Exploring Multimodal Turn-Taking Cues in Face-to-Face Conversation using Voice Activity Projection
Turn-taking is a fundamental component of spoken interaction, and while humans naturally rely on both verbal and non-verbal signals, dialogue systems usually depend on audio cues alone.Parameter isolation with domain-specific experts for incremental audio classification
To successfully deploy a model in time-varying environments such as streaming data prediction and sensing control, domain-incremental learning (DIL) has attracted attention since it aims to adapt a…CCMAN: Cognitive Instability-Aware Cross-Modal Attention Network for Interpretable Temporal Biomarkers of Verbal Fluency Speech
Early detection of cognitive decline from speech offers a scalable and non-invasive alternative to conventional clinical assessment.POLARIS: Training-Free Audio Fingerprinting with Saliency-Based Landmarks and Delaunay Grouping
This work presents POLARIS, a training-free audio fingerprinting system that selects landmarks from a locally normalized saliency field and groups them into sparse fingerprints using Delaunay…UniqueShip: Mitigating Data Leakage in Acoustic Ship Classification Benchmark Datasets
Underwater Acoustic Target Recognition (UATR) of ships is well-suited for machine learning, yet its progress is hindered by the lack of large, diverse, and publicly available labeled datasets.CRAF: Cross-View Residual-Aware Fusion for Deepfake Speech Detection
Recent advances in speech synthesis and voice conversion have made deepfake speech increasingly realistic, making generalization to unseen spoofing attacks a critical challenge.DiTAR+: Dual Optimization for Robust Autoregressive Diffusion Speech Synthesis
Continuous-latent Autoregressive Diffusion Transformer (AR-DiT) models have demonstrated immense potential in zero-shot speech generation.A New Transformer-Based Approach for Audio-Based Kinship Verification and a New Uncontrolled Mandarin Kinship Speech Dataset
Kinship verification is a task involving determining whether two individuals share a first-order kin relation.Inherited Heads: Audio language models track speakers with their text backbone's attention, and an attention-mass ranking retrieves a different set
Asked to describe what one of six speakers in a recording talks about, audio language models describe the right one on 6 to 16% of trials, below the 16.7% a guess would give.