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eess.AS updates on arXiv.org

Dependence on Early and Late Reverberation of Single-Channel Speaker Distance Estimation MIST: Multimodal Interactive Speech-based Tool-calling Conversational Assistants for Smart Homes LiVeAction: a Lightweight, Versatile, and Asymmetric Neural Codec Design for Real-time Operation Weight-Decay Turns Transformer Loss Landscapes Villani: Functional-Analytic Foundations for Optimization and Generalization PairAlign: A Framework for Sequence Tokenization via Self-Alignment with Applications to Audio Tokenization WavCube: Unifying Speech Representation for Understanding and Generation via Semantic-Acoustic Joint Modeling Predictive-Generative Drift Decomposition for Speech Enhancement and Separation Minimizing Modality Gap from the Input Side: Your Speech LLM Can Be a Prosody-Aware Text LLM X-Voice: Enabling Everyone to Speak 30 Languages via Zero-Shot Cross-Lingual Voice Cloning JASTIN: Aligning LLMs for Zero-Shot Audio and Speech Evaluation via Natural Language Instructions Phoneme-Level Deepfake Detection Across Emotional Conditions Using Self-Supervised Embeddings When Audio-Language Models Fail to Leverage Multimodal Context for Dysarthric Speech Recognition Dimensionality-Aware Anomaly Detection in Learned Representations of Self-Supervised Speech Models Mitigating Multimodal LLMs Hallucinations via Relevance Propagation at Inference Time Virtual Speech Therapist: A Clinician-in-the-Loop AI Speech Therapy Agent for Personalized and Supervised Therapy LASE: Language-Adversarial Speaker Encoding for Indic Cross-Script Identity Preservation Towards Improving Speaker Distance Estimation through Generative Impulse Response Augmentation Beyond Decodability: Reconstructing Language Model Representations with an Encoding Probe MMAudioReverbs: Video-Guided Acoustic Modeling for Dereverberation and Room Impulse Response Estimation Alethia: A Foundational Encoder for Voice Deepfakes From Birdsong to Rumbles: Classifying Elephant Calls with Out-of-Species Embeddings Beyond the Baseband: Adaptive Multi-Band Encoding for Full-Spectrum Bioacoustics Classification Predicting Upcoming Stuttering Events from Three-Second Audio: Stratified Evaluation Reveals Severity-Selective Precursors, and the Model Deploys Fully On-Device The False Resonance: A Critical Examination of Emotion Embedding Similarity for Speech Generation Evaluation DiffAnon: Diffusion-based Prosody Control for Voice Anonymization Recurrence-Based Nonlinear Vocal Dynamics as Digital Biomarkers for Depression Detection from Conversational Speech One Voice, Many Tongues: Cross-Lingual Voice Cloning for Scientific Speech Similarity Choice and Negative Scaling in Supervised Contrastive Learning for Deepfake Audio Detection Walking Through Uncertainty: An Empirical Study of Uncertainty Estimation for Audio-Aware Large Language Models Praxy Voice: Voice-Prompt Recovery + BUPS for Commercial-Class Indic TTS from a Frozen Non-Indic Base at Zero Commercial-Training-Data Cost ML-SAN: Multi-Level Speaker-Adaptive Network for Emotion Recognition in Conversations Korean aegyo speech shows systematic F1 increase to signal childlike qualities All That Glitters Is Not Audio: Rethinking Text Priors and Audio Reliance in Audio-Language Evaluation Speech Enhancement Based on Drifting Models Talker-T2AV: Joint Talking Audio-Video Generation with Autoregressive Diffusion Modeling Explainable AI in Speaker Recognition -- Making Latent Representations Understandable TTS-PRISM: A Perceptual Reasoning and Interpretable Speech Model for Fine-Grained Diagnosis UniSonate: A Unified Model for Speech, Music, and Sound Effect Generation with Text Instructions Dilated CNNs for Periodic Signal Processing: A Low-Complexity Approach ONOTE: Benchmarking Omnimodal Notation Processing for Expert-level Music Intelligence MoDAl: Self-Supervised Neural Modality Discovery via Decorrelation for Speech Neuroprosthesis Voice Mapping of Text-to-Speech Systems: A Metric-Based Approach for Voice Quality Assessment UAF: A Unified Audio Front-end LLM for Full-Duplex Speech Interaction Voice of India: A Large-Scale Benchmark for Real-World Speech Recognition in India Reducing the Offline-Streaming Gap for Unified ASR Transducer with Consistency Regularization Audio2Tool: Speak, Call, Act -- A Dataset for Benchmarking Speech Tool Use Qwen3.5-Omni Technical Report Speech Emotion Recognition Using MFCC Features and LSTM-Based Deep Learning Model The Acoustic Camouflage Phenomenon: Re-evaluating Speech Features for Financial Risk Prediction SongBench: A Fine-Grained Multi-Aspect Benchmark for Song Quality Assessment VoxSafeBench: Not Just What Is Said, but Who, How, and Where In-Sync: Adaptation of Speech Aware Large Language Models for ASR with Word Level Timestamp Predictions MoshiRAG: Asynchronous Knowledge Retrieval for Full-Duplex Speech Language Models X-VC: Zero-shot Streaming Voice Conversion in Codec Space Audio Flamingo Next: Next-Generation Open Audio-Language Models for Speech, Sound, and Music ASPIRin: Action Space Projection for Interactivity-Optimized Reinforcement Learning in Full-Duplex Speech Language Models Utterance-Level Methods for Identifying Reliable ASR-Output for Child Speech Enhancing ASR Performance in the Medical Domain for Dravidian Languages PS-TTS: Phonetic Synchronization in Text-to-Speech for Achieving Natural Automated Dubbing Disentangled Dual-Branch Graph Learning for Conversational Emotion Recognition OmniVoice: Towards Omnilingual Zero-Shot Text-to-Speech with Diffusion Language Models HARNESS: Lightweight Distilled Arabic Speech Foundation Models KoALa-Bench: Evaluating Large Audio Language Models on Korean Speech Understanding and Faithfulness Explainable Speech Emotion Recognition: Weighted Attribute Fairness to Model Demographic Contributions to Social Bias The Silent Thought: Modeling Internal Cognition in Full-Duplex Spoken Dialogue Models via Latent Reasoning Something from Nothing: Data Augmentation for Robust Severity Level Estimation of Dysarthric Speech Interpreting Speaker Characteristics in the Dimensions of Self-Supervised Speech Features From Black Box to Glass Box: Cross-Model ASR Disagreement to Prioto Review in Ambient AI Scribe Documentation WST-X Series: Wavelet Scattering Transform for Interpretable Speech Deepfake Detection Kanade: A Simple Disentangled Tokenizer for Spoken Language Modeling AQUA-Bench: Beyond Finding Answers to Knowing When There Are None in Audio Question Answering Diagnostic-Driven Layer-Wise Compensation for Post-Training Quantization of Encoder-Decoder ASR Models BERT-APC: A Reference-free Framework for Automatic Pitch Correction via Musical Context Inference MTR-DuplexBench: Towards a Comprehensive Evaluation of Multi-Round Conversations for Full-Duplex Speech Language Models Sound Source Localization for Spatial Mapping of Surgical Actions in Dynamic Scenes Gelina: Unified Speech and Gesture Synthesis via Interleaved Token Prediction Efficient Test-Time Adaptation through Latent Subspace Coefficients Search MMAudioSep: Taming Video-to-Audio Generative Model Towards Video/Text-Queried Sound Separation VAPO: End-to-end Slide-Enhanced Speech Recognition with Omni-modal Large Language Models TokenChain: A Discrete Speech Chain via Semantic Token Modeling BaldWhisper: Faster Whisper with Head Shearing and Layer Merging Game-Time: Evaluating Temporal Dynamics in Spoken Language Models Zero-Effort Image-to-Music Generation: An Interpretable RAG-based VLM Approach Direct Simultaneous Translation Activation for Large Audio-Language Models CodecSep: Prompt-Driven Universal Sound Separation on Neural Audio Codec Latents Joint Learning using Mixture-of-Expert-Based Representation for Speech Enhancement and Robust Emotion Recognition DreamAudio: Customized Text-to-Audio Generation with Diffusion Models Computational Narrative Understanding for Expressive Text-to-Speech Gaussian Process Regression of Steering Vectors With Physics-Aware Deep Composite Kernels for Augmented Listening Balalaika: Data-Centric, Prosody-Aware Annotation Pipeline for Russian Speech Towards Holistic Evaluation of Large Audio-Language Models: A Comprehensive Survey FMSD-TTS: Few-shot Multi-Speaker Multi-Dialect Text-to-Speech Synthesis for Ü-Tsang, Amdo and Kham Speech Dataset Generation Not that Groove: Zero-Shot Symbolic Music Editing Speculative End-Turn Detector for Efficient Speech Chatbot Assistant AudioX: A Unified Framework for Anything-to-Audio Generation S2S-Arena: Evaluating Paralinguistic Instruction Following in Speech-to-Speech Models Throat and acoustic paired speech dataset for deep learning-based speech enhancement Dementia classification from spontaneous speech using wrapper-based feature selection DASB - Discrete Audio and Speech Benchmark Basic syntax from speech: Spontaneous concatenation in unsupervised deep neural networks
Model-based Speech Enhancement for Intelligibility Improvement in Binaural Hearing Aids
Mathew Shaji Kavalekalam, Jesper K. Nielsen, Jesper B. Boldt, Ma · 2018-06-13 · via eess.AS updates on arXiv.org

Speech intelligibility is often severely degraded among hearing impaired individuals in situations such as the cocktail party scenario. The performance of the current hearing aid technology has been observed to be limited in these scenarios. In this paper, we propose a binaural speech enhancement framework that takes into consideration the speech production model. The enhancement framework proposed here is based on the Kalman filter that allows us to take the speech production dynamics into account during the enhancement process. The usage of a Kalman filter requires the estimation of clean speech and noise short term predictor (STP) parameters, and the clean speech pitch parameters. In this work, a binaural codebook-based method is proposed for estimating the STP parameters, and a directional pitch estimator based on the harmonic model and maximum likelihood principle is used to estimate the pitch parameters. The proposed method for estimating the STP and pitch parameters jointly uses the information from left and right ears, leading to a more robust estimation of the filter parameters. Objective measures such as PESQ and STOI have been used to evaluate the enhancement framework in different acoustic scenarios representative of the cocktail party scenario. We have also conducted subjective listening tests on a set of nine normal hearing subjects, to evaluate the performance in terms of intelligibility and quality improvement. The listening tests show that the proposed algorithm, even with access to only a single channel noisy observation, significantly improves the overall speech quality, and the speech intelligibility by up to 15%.