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cs.SD updates on arXiv.org

Mutual Forcing: Dual-Mode Self-Evolution for Fast Autoregressive Audio-Video Character Generation WhisperPipe: A Resource-Efficient Streaming Architecture for Real-Time Automatic Speech Recognition Walking Through Uncertainty: An Empirical Study of Uncertainty Estimation for Audio-Aware Large Language Models PSP: An Interpretable Per-Dimension Accent Benchmark for Indic Text-to-Speech Praxy Voice: Voice-Prompt Recovery + BUPS for Commercial-Class Indic TTS from a Frozen Non-Indic Base at Zero Commercial-Training-Data Cost 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 RAS: a Reliability Oriented Metric for Automatic Speech Recognition Speech Enhancement Based on Drifting Models HeadRouter: Dynamic Head-Weight Routing for Task-Adaptive Audio Token Pruning in Large Audio Language Models Hallo-Live: Real-Time Streaming Joint Audio-Video Avatar Generation with Asynchronous Dual-Stream and Human-Centric Preference Distillation Talker-T2AV: Joint Talking Audio-Video Generation with Autoregressive Diffusion Modeling Robust Audio-Text Retrieval via Cross-Modal Attention and Hybrid Loss Spectro-Temporal Modulation Representation Framework for Human-Imitated Speech Detection UniSonate: A Unified Model for Speech, Music, and Sound Effect Generation with Text Instructions Do LLM Decoders Listen Fairly? Benchmarking How Language Model Priors Shape Bias in Speech Recognition Materialistic RIR: Material Conditioned Realistic RIR Generation SpeechParaling-Bench: A Comprehensive Benchmark for Paralinguistic-Aware Speech Generation ONOTE: Benchmarking Omnimodal Notation Processing for Expert-level Music Intelligence From Image to Music Language: A Two-Stage Structure Decoding Approach for Complex Polyphonic OMR ATIR: Towards Audio-Text Interleaved Contextual Retrieval Enhancing Speaker Verification with Whispered Speech via Post-Processing Environmental Sound Deepfake Detection Using Deep-Learning Framework Towards Streaming Target Speaker Extraction via Chunk-wise Interleaved Splicing of Autoregressive Language Model BEAT: Tokenizing and Generating Symbolic Music by Uniform Temporal Steps Deep Supervised Contrastive Learning of Pitch Contours for Robust Pitch Accent Classification in Seoul Korean HalluAudio: A Comprehensive Benchmark for Hallucination Detection in Large Audio-Language Models 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 Tadabur: A Large-Scale Quran Audio Dataset Comparison of sEMG Encoding Accuracy Across Speech Modes Using Articulatory and Phoneme Features Video-Robin: Autoregressive Diffusion Planning for Intent-Grounded Video-to-Music Generation Virtual boundary integral neural network for three-dimensional exterior acoustic problems Audio2Tool: Speak, Call, Act -- A Dataset for Benchmarking Speech Tool Use AST: Adaptive, Seamless, and Training-Free Precise Speech Editing Breakout-picker: Reducing false positives in deep learning-based borehole breakout characterization from acoustic image logs Hierarchical Codec Diffusion for Video-to-Speech Generation ControlFoley: Unified and Controllable Video-to-Audio Generation with Cross-Modal Conflict Handling From Reactive to Proactive: Assessing the Proactivity of Voice Agents via ProVoice-Bench The Acoustic Camouflage Phenomenon: Re-evaluating Speech Features for Financial Risk Prediction Hijacking Large Audio-Language Models via Context-Agnostic and Imperceptible Auditory Prompt Injection TurboTalk: Progressive Distillation for One-Step Audio-Driven Talking Avatar Generation Temporal Contrastive Decoding: A Training-Free Method for Large Audio-Language Models VoxSafeBench: Not Just What Is Said, but Who, How, and Where Elderly-Contextual Data Augmentation via Speech Synthesis for Elderly ASR Towards Fine-grained Temporal Perception: Post-Training Large Audio-Language Models with Audio-Side Time Prompt Comparison of window shapes and lengths in short-time feature extraction for classification of heart sound signals In-Sync: Adaptation of Speech Aware Large Language Models for ASR with Word Level Timestamp Predictions Graph Propagated Projection Unlearning: A Unified Framework for Vision and Audio Discriminative Models HHL with a Coherent Fourier Oracle: A Proof-of-Concept Quantum Architecture for Joint Melody-Harmony Generation ActorMind: Emulating Human Actor Reasoning for Speech Role-Playing Efficient Training for Cross-lingual Speech Language Models Audio Flamingo Next: Next-Generation Open Audio-Language Models for Speech, Sound, and Music MeloTune: On-Device Arousal Learning and Peer-to-Peer Mood Coupling for Proactive Music Curation BlasBench: An Open Benchmark for Irish Speech Recognition Audio-Omni: Extending Multi-modal Understanding to Versatile Audio Generation and Editing Knowing What to Stress: A Discourse-Conditioned Text-to-Speech Benchmark VidAudio-Bench: Benchmarking V2A and VT2A Generation across Four Audio Categories Cross-Cultural Bias in Mel-Scale Representations: Evidence and Alternatives from Speech and Music Beyond Monologue: Interactive Talking-Listening Avatar Generation with Conversational Audio Context-Aware Kernels ASPIRin: Action Space Projection for Interactivity-Optimized Reinforcement Learning in Full-Duplex Speech Language Models Interactive ASR: Towards Human-Like Interaction and Semantic Coherence Evaluation for Agentic Speech Recognition Tora3: Trajectory-Guided Audio-Video Generation with Physical Coherence Disentangled Dual-Branch Graph Learning for Conversational Emotion Recognition Real-Time Voicemail Detection in Telephony Audio Using Temporal Speech Activity Features Woosh: A Sound Effects Foundation Model KoALa-Bench: Evaluating Large Audio Language Models on Korean Speech Understanding and Faithfulness From Black Box to Glass Box: Cross-Model ASR Disagreement to Prioto Review in Ambient AI Scribe Documentation Diagnostic-Driven Layer-Wise Compensation for Post-Training Quantization of Encoder-Decoder ASR Models Style Amnesia: Investigating Speaking Style Degradation and Mitigation in Multi-Turn Spoken Language Models Real-Time Streamable Generative Speech Restoration with Flow Matching Hearing to Translate: The Effectiveness of Speech Modality Integration into LLMs Protecting Bystander Privacy via Selective Hearing in Audio LLMs Language Models as Semantic Teachers: Post-Training Alignment for Medical Audio Understanding BERT-APC: A Reference-free Framework for Automatic Pitch Correction via Musical Context Inference Musical Score Understanding Benchmark: Evaluating Large Language Models' Comprehension of Complete Musical Scores 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 Data-efficient Targeted Token-level Preference Optimization for LLM-based Text-to-Speech When Silence Matters: The Impact of Irrelevant Audio on Text Reasoning in Large Audio-Language Models MARS: Sound Generation via Multi-Channel Autoregression on Spectrograms Zero-Effort Image-to-Music Generation: An Interpretable RAG-based VLM Approach StableToken: A Noise-Robust Semantic Speech Tokenizer for Resilient SpeechLLMs CoMelSinger: Discrete Token-Based Zero-Shot Singing Synthesis With Structured Melody Control and Guidance RFM-Editing: Rectified Flow Matching for Text-guided Audio Editing CodecSep: Prompt-Driven Universal Sound Separation on Neural Audio Codec Latents 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 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 Sat2Sound: A Unified Framework for Zero-Shot Soundscape Mapping Histogram-based Parameter-efficient Tuning for Passive and Active Sonar Classification Speculative End-Turn Detector for Efficient Speech Chatbot Assistant AudioX: A Unified Framework for Anything-to-Audio Generation Speech-FT: Merging Pre-trained And Fine-Tuned Speech Representation Models For Cross-Task Generalization 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
Revolutionizing Personalized Voice Synthesis: The Journey towards Emotional and Individual Authenticity with DIVSE (Dynamic Individual Voice Synthesis Engine)
Fan Shi · 2023-12-28 · via cs.SD updates on arXiv.org

This comprehensive paper delves into the forefront of personalized voice synthesis within artificial intelligence (AI), spotlighting the Dynamic Individual Voice Synthesis Engine (DIVSE). DIVSE represents a groundbreaking leap in text-to-voice (TTS) technology, uniquely focusing on adapting and personalizing voice outputs to match individual vocal characteristics. The research underlines the gap in current AI-generated voices, which, while technically advanced, fall short in replicating the unique individuality and expressiveness intrinsic to human speech. It outlines the challenges and advancements in personalized voice synthesis, emphasizing the importance of emotional expressiveness, accent and dialect variability, and capturing individual voice traits. The architecture of DIVSE is meticulously detailed, showcasing its three core components: Voice Characteristic Learning Module (VCLM), Emotional Tone and Accent Adaptation Module (ETAAM), and Dynamic Speech Synthesis Engine (DSSE). The innovative approach of DIVSE lies in its adaptive learning capability, which evolves over time to tailor voice outputs to specific user traits. The paper presents a rigorous experimental setup, utilizing accepted datasets and personalization metrics like Mean Opinion Score (MOS) and Emotional Alignment Score, to validate DIVSE's superiority over mainstream models. The results depict a clear advancement in achieving higher personalization and emotional resonance in AI-generated voices.

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