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.
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Newest papers, page 4
Muting Tokens: Exploring Token Sparsification for Efficient Audio Transformers
Transformer-based models have shown strong performance across diverse tasks, but their reliance on self-attention mechanisms often leads to high computational costs.Decodability Is Not Controllability: Local and Anisotropic Speaker Control in Continuous-Latent TTS
High linear decodability does not entail causal controllability in continuous-latent text-to-speech (TTS).Closed-Loop Dual-Reference Guidance for Accent Control in Cross-Lingual Voice Cloning
Zero-shot cross-lingual voice cloning often carries the reference speaker's accent into the target language.Bio-Inspired Auditory Processing: Coupling Parallel Resonate-and-Fire Dynamics with Ternary Recurrent Networks for Speech Recognition
Spiking Neural Networks (SNNs) promise energy-efficient inference through sparse, event-driven computation, yet remain constrained on continuous, context-dependent tasks such as automatic speech…NeuroCodec: EEG-Guided Latent-Domain Generative Model for High-Fidelity Target Speaker Extraction
Driven by recent advancements in hearing assistive devices, target speaker extraction (TSE) in multi-talker environments has drawn significant attention.SMART: Semantic Segment Mapping and Assessment of Recognition Transcripts with Contextual Rubrics
Word error rate (WER) assigns equal cost to lexical edits despite their different semantic consequences, while overall semantic scores cannot identify which individual errors alter the intended…VISH-ASR: Viterbi-Guided Selection of Hotwords for Speech-LLM Contextual ASR
Prompt-based contextual ASR requires selecting a compact hotword subset from large dynamic inventories, yet existing pre-selection methods rely either on discrete ASR hypotheses that may discard…Uncovering Audio-Text Alignment in Large Audio-Language Models through Cross-Modal Concept Neurons
While the language model backbone is pretrained on text alone, large audio-language models (LALMs) can, to a great extent, recognize acoustic attributes, such as emotion, speaker gender, and spoken…Manifold-Constrained Residual Adaptation with Frame-Adaptive Layer Aggregation for Speaker Verification
Large self-supervised speech models provide powerful representations for speaker verification, but full fine-tuning is expensive.Multilingual Voicemail and Answering Machine Detection via Pretrained Audio Embeddings and Gradient Boosting Machines
Answering machine detection (AMD) is a fundamental task in telephony that classifies whether an answered call is picked up by a human or a voicemail (machine).AudioScorer: Learning Question-Aware Token Relevance for Large Audio Language Models
Large Audio Language Models (LALMs) reason over speech, environmental sounds, music, and other acoustic information.Label Authority in Speech Emotion Recognition: Intended and Perceived Ground Truth in Emozionalmente
Ground truth in Speech Emotion Recognition (SER) is often presented as a single categorical fact, yet an acted emotion and the emotion heard by listeners describe different aspects of the same…TeleASR-Amharic: A Benchmark for Robust Amharic ASR in Realistic Telecommunication Conditions
The real-world usability of ASR models remains challenging, particularly for low-resource languages, where existing speech resources are often collected in clean studio environments.Beyond Two Tracks: Speaker-Anchored Full-Duplex Dialogue Recovery
Spoken interaction is moving from alternating turns to full-duplex conversation, where an agent listens while speaking.DF-PALM: Dynamic Fusion Prompt Learning for Audio--Language Models
Few-shot audio classification requires audio--language models to distinguish variable acoustic events from limited labeled data.Shared-Private Cross-Modal Discrepancy Learning for Imbalanced Multi-Source Audio-Visual Deepfake Detection
Audio-visual deepfake detectors are often trained under a single dataset or manipulation regime, but multi-source training collections may contain heterogeneous attacks and uneven source…CASE: Complementary Articulation-Aware Speech Encoder to Enhance Speech-Driven 3D Facial Animation
General-purpose self-supervised speech encoders provide strong acoustic representations, but their pretraining objectives are not explicitly aligned with the visible articulatory dynamics required…How Far Can the Gemma 4 Speech Encoder Go Without Changing Its Weights? Saudi and Gulf Arabic Speech Recognition with a Frozen and an Adapter-Augmented Encoder
We study the 305M-parameter audio encoder shared by Gemma 4 and EmbeddingGemma 2 (identical except for its final projection) for Saudi and Gulf Arabic speech recognition, without changing any of its…Long Listening Thoughts: Eliciting Open Auditory Reasoning with Deliberative Perception and Cognitive Refinement
We introduce Long Listening Thoughts (LLT), a framework for constructing post-training datasets that improves audio reasoning by pairing deliberate perceptual grounding with explicit cognitive…SENTRY: A Streaming Edge Network Trust Engine for Real-Time Audio Deepfake Detection
Real-time voice cloning has enabled large-scale streaming deepfake and vishing attacks, while existing Network Detection and Response (NDR) solutions rely on GPU-based post-processing that requires…