Hugging Face Trending Papers
Preference Optimization for Non-Verbal Vocalization Synthesis
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arXiv AI
Aug 26
Preference Optimization for Non-Verbal Vocalization Synthesis
The paper investigates how to optimize non‑verbal vocalizations (NVs) such as laughter, coughs, and sighs in text‑to‑speech systems. It introduces a preference‑optimization framework that uses preference signals, pair construction, and DPO objectives, and defines an NV‑aware character error rate (NV‑CER) to guide controllable NV generation. Experiments on Emilia‑NV and NV‑Bench demonstrate that the proposed setup improves NV realization and lexical fidelity, with objective, LLM‑based, and human evaluations supporting the results.
arXiv AI
Sep 15
Modeling, Scaling, and Decoding: Optimizing Controllable Speech Generation with Nonverbal Vocalizations
arXiv:2609.14231v1 Announce Type: cross Abstract: Controllable synthesis of nonverbal vocalizations (NVVs) is es- sential for natural and expressive speech, but remains challeng- ing due to their aco...
arXiv Machine Learning
Jun 17
CoCoEmo: Composable and Controllable Human-Like Emotional TTS via Activation Steering
arXiv:2602. 03420v2 Announce Type: replace-cross Abstract: Emotional expression in human speech is nuanced and compositional, often involving multiple, sometimes conflicting, affective cues that may diverge from linguistic content.
arXiv Machine Learning
Jul 1
Is Natural Always Appropriate? Investigating Naturalness and Appropriateness Across Different Domains for TTS Evaluation
arXiv:2606. 31729v1 Announce Type: cross Abstract: Text-to-speech (TTS) evaluation is an open challenge.
arXiv Computation and Language
Sep 2
Ready to Speak: Aligning LLMs for TTS-Friendly Text Generation
arXiv:2609.01246v1 Announce Type: new Abstract: Current Large Language Models (LLMs) are primarily optimized for written text, often producing outputs that are grammatically correct and helpful yet p...
arXiv AI
Sep 18
Multi-Dimensional Prosody Judgment For Live Streaming Speech Synthesis
The paper introduces Live-ProsodyJudge (LPJ), a cost‑effective pairwise evaluator distilled from Gemini for assessing fine‑grained prosody in live streaming TTS. It identifies a flaw called verdict coupling, where multi‑dimensional scores collapse into a single preference, and proposes Decoupled‑Live‑ProsodyJudge (D‑LPJ) to eliminate this issue through masking and a span‑local GRPO strategy. Experiments show LPJ outperforms a single Gemini call in accuracy, and D‑LPJ provides independent dimension judgments, achieving high alignment with human top‑3 selections in a TTS candidate tournament.