Vagdhenu is a Sanskrit shloka‑to‑chant text‑to‑speech system that preserves meter (vrutta) and phonological nuances. It builds on an off‑the‑shelf flow‑matching backbone and a large‑scale neural vocoder, adding a Kannada‑based frontend to avoid schwa deletion, a phonology‑aware frontend handling visarga sandhi and sibilant distinctions, and a vrutta‑aware reference selection mechanism. The authors report that a text‑side prosody conditioner is ineffective in their architecture, while reference clips and voice‑steering retraining provide the necessary prosody control, and they demonstrate the system’s performance on a 32‑chapter video corpus and an audio app covering 18,000 verses.
whyItMatters":"The system delivers high‑fidelity, meter‑aware Sanskrit chanting, enabling large‑scale deployment of authentic recitations for educational and cultural preservation purposes."
By Prathosh A P
PARSA‑Bench is the first dedicated benchmark for evaluating large audio‑language models on Persian, addressing unique challenges such as classical poetry, traditional music, and code‑switching. It comprises 16 tasks—10 of which are new—covering speech understanding, paralinguistic analysis, and culturally grounded audio reasoning. Across most tasks, text‑only baselines outperform audio‑based models, indicating that audio understanding remains the main limitation, except for Persian poetry where prosody provides additional information that audio beats text.
By Mohammad Javad Ranjbar Kalahroodi, Mohammad Amini, Parmis Bathayan, Heshaam Faili, Azadeh Shakery
arXiv:2510.10774v4 Announce Type: replace-cross
Abstract: Persian remains substantially underrepresented in open speech-text resources, limiting progress in multi-speaker text-to-speech (TTS), speech...
By Mohammad Javad Ranjbar Kalahroodi, Heshaam Faili, Azadeh Shakery
arXiv:2610.14826v1 Announce Type: cross
Abstract: Recent alignment-free Text-to-Speech (TTS) models achieve high synthesis quality by removing explicit alignment modules and simplifying training. How...
By Adarsh Arigala, Arjun Gangwar, Srinivasan Umesh
While large language model (LLM)-based text-to-speech (TTS) systems have achieved high-quality speech synthesis, most existing systems focus on English and Chinese. Japanese, however, remains under-explored, and its unique linguistic challenges, such as widespread context-dependent kanji polyphony, have yet to be adequately tackled.
arXiv:2605. 13087v2 Announce Type: replace-cross Abstract: Fine-tuning multilingual ASR models like Whisper for low-resource languages often improves read speech but degrades spontaneous audio performance.
By Kush Juvekar, Kavya Manohar, Aditya Srinivas Menon, Arghya Bhattacharya, Kumarmanas Nethil
arXiv:2606. 26144v1 Announce Type: cross Abstract: Speaker diarization, the task of determining "who spoke when" in a multi-speaker recording, is a critical component in applications such as meeting transcription, accessibility tools, and multilingual information retrieval.
By Samip Neupane, Sandesh Pokhrel, Sandesh Pyakurel, Basanta Joshi
arXiv:2507.02115v3 Announce Type: cross
Abstract: Synthesizing second-language (L2) speech is potentially highly valued for L2 language learning experience and feedback. However, due to the lack of L...
By Zirui Li, Lauri Juvela, Mikko Kurimo
arXiv:2609.23951v1 Announce Type: new
Abstract: Expressive speech synthesis has advanced through prosody modeling, yet generating structured poetic speech, such as haiku, remains challenging. Prior w...
By Devangi Sharma, Sophia Judicke, Glenda Tan, Conrad Schaumburg, Shinji Watanabe
arXiv:2608. 02235v1 Announce Type: cross Abstract: Recent advances in neural text-to-speech (TTS) systems have substantially improved speech naturalness and intelligibility across many languages.
By Ali Jafar, Amal Sarmad, Shifa Yousaf, Maryam Bashir
arXiv:2607. 23808v1 Announce Type: cross Abstract: In this work, we introduce Indic DiarBench, a speaker diarization and ASR benchmark dataset spanning all 22 scheduled languages of India.
By Deovrat Mehendale, Aditya Mehndiratta, Dhruv Rathi, Kaushal Bhogale, Mitesh M. Khapra
arXiv:2610.09756v1 Announce Type: new
Abstract: Classical Arabic poetry generation requires simultaneously satisfying semantic, linguistic, and fine-grained prosodic constraints. Existing systems typ...
By Ahmad Abbas, Tamara Fakih, Nour Fakih, Ammar Mohanna