Engineering & Signals · Interdisciplinary & Society
Audio & Speech Processing
The newest papers in Audio & Speech Processing that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
334 papers, from 8 September 2026 to 4 November 2026: 334 arXiv preprints.
Get the few papers worth your time in Audio & Speech Processing every morning.
Follow Audio & Speech Processing 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 7
Does Financial Speech Need Continual Learning Regularization? A Study of EWC and mini-KFAC on Earnings Call ASR
Earnings call transcription presents a realistic continual learning scenario where Automatic Speech Recognition (ASR) systems are updated with new recordings but risk catastrophic forgetting of…Revisiting Accent Classification with DistilHuBERT: Speaker-Disjoint Evaluation and Cross-Corpus Generalization
Recent accent classification systems can achieve high accuracy in standard in-corpus evaluations.Oído: Open-Vocabulary Speech Recognition on a $5 Microcontroller without a Neural Accelerator
Speech recognition on low-cost microcontrollers is, in practice, limited to keyword spotting or a fixed list of commands.AudioTETRIS: Token Elimination via Transitional Importance Signals for Efficient Audio LLMs
Large Audio Language Models (LALMs) achieve strong performance on speech-text tasks, but standard audio encoders produce hundreds of tokens for even short audio clips.Vocal Intensity Conversion with Continuous SPL Control via Adversarial Training
Vocal intensity conversion renders a recorded utterance at a different vocal intensity, rather than simply scaling its amplitude, while preserving its content and speaker identity.OpenPA: Forced-alignment-free Multi-granular Pronunciation Assessment with Mixed-transcript Adaptation
Recent advances in automatic pronunciation assessment (APA) have driven a shift from scripted to free-form assessment.RUBATO: Decoupled Clocks Allow Full-Duplex Models to Think as Fast as They Can
Recent Speech Full-Duplex (FDX) models are capable of engaging in naturalistic conversation by listening and speaking at the same time.Beyond Speech Captions: Speech-Rewarded Style Planning for Conversational Text-to-Speech
Natural-language style descriptions provide an interpretable interface between large language models (LLMs) and controllable text-to-speech (TTS).SteerablePlex: Can We Steer Full-Duplex Models?
Full-duplex speech models can listen and speak simultaneously, enabling natural interaction, but become increasingly difficult to control as the conversation history grows.Structural and Representational Agency in LLM-Driven Timbre Generation and Interpolation
Generative creative interfaces routinely report the user's position within a space of possibilities.Efficient Audio-Visual Speech Enhancement via Reinforcement Learning-Based Neural Architecture Search
Audio-visual speech enhancement (AVSE) improves speech intelligibility in noisy environments but often relies on computationally expensive models unsuitable for resource-constrained edge devices.Spend Where It Matters: Particle Search with MH Refinement for Budget-Constrained Audio-Visual Alignment
Reward-guided inference-time alignment can improve joint audio-visual generation, but optimizing multiple alignment objectives requires many expensive model evaluations, making existing methods…Two-Stage Multi-modal Learning for Dynamic Audio-Visual Navigation: From Physical Alignment to Scene Aggregation
Embodied Audio-Visual Navigation (AVN) requires an agent to locate sound targets by jointly leveraging visual and auditory cues.Dialect-Robust Speech Language Models with Synthetic Pseudo-Dialect Augmentation
Speech Language Model (SLM) performance often degrades on dialects due to data scarcity.VM-ARRAYDPS: Virtual Microphone Augmented Diffusion Posterior Sampling for Unsupervised Blind Speech Separation
Blind Source Separation(BSS) is a fundamental problem in signal processing, aiming to separate multiple source signals from their mixtures without prior knowledge of the sources or the mixing process.Boundary-Free Contextual Biasing: Depth-Adaptive Gating and Reading-Space Matching for Unsegmented Languages
Contextual biasing supplies an ASR system with a list of expected words at inference time, but existing methods rely on word boundaries that Japanese and Chinese do not provide.Mitigating Accent-Language Confusion in Self-Supervised Speech Representations for Language Identification
Spoken language identification (LID) aims to recognize the target language regardless of accent.Tracing Inputs, Verifying Outputs: Validating Attribution in Music Generation
How can we verify whose music contributed to an AI-generated output?A Strength-Monotonic Law for Domain Alignment in Frozen-Embedding Bioacoustic Classification
When does distribution alignment help a frozen foundation-model embedding generalize across acoustic domains?Steerspeech: Activation Steering For Emotion Control In Generated Speech
Pretrained text-to-speech (TTS) models can generate expressive speech, but reliable inference-time emotion control remains challenging: prompts and reference audio offer coarse, inconsistent…