Scaling ASR for Hutsul Dialect: Multi-Speaker Data Collection, Enhanced Transcription and Cross-Speaker Evaluation

Open access Aug 2026

Persona-ASR: Bilingual Target-Speaker Speech Recognition for Kazakh–English Overlapping Speech

To the authors' knowledge, Persona-ASR is the first TS-ASR system for the Kazakh language, establishing a foundation for multilingual personalized ASR in low-resource settings.

Rakhat Meiramov, Tomiris Rakhimzhanova, Adil Taibassarov et al. · Machine Learning and Knowled... · 0 citations

Preprint Aug 2026

DiaScriber: A Speech LLM for Joint Diarization and Transcription in Multi-Speaker Scenarios

DiaScriber is proposed, an end-to-end multi-speaker diarization and transcription model built on a speech large language model that achieves superior performance over comparison methods across extensive multi-speaker scenario test sets and demonstrates outstanding generalization ability in unseen multi-speaker scenario...

Bing-Shen Mu, Xian Shi, Xiong Wang et al. · 0 citations

Preprint Jul 2026

Diarization-Guided Qwen-ASR Adaptation for Multilingual Two-Speaker Conversational Speech

Results show that supervised fine-tuning provides the largest gain, while synthetic-speech LoRA adaptation and reinforcement learning further improve robustness, while synthetic-speech LoRA adaptation and reinforcement learning further improve robustness.

Hao Wu, Rong-Qi Han, Zhen Wang et al. · 0 citations

Open access Jul 2026

A Nepali-Accented English Evaluation Dataset for Automatic Speech Recognition

A Nepali-accented English evaluation dataset designed to support robust ASR benchmarking under accent mismatch is presented, positioning the corpus as a practical held-out resource for evaluating accent robustness and out-of-distribution generalization on Nepali-accented English.

Santosh Dahal, K. Dahal · Everest Advances in Science... · 0 citations

Preprint Aug 2026

SraVaani 1.0: Scaling Inclusive Speech Recognition for Indic Languages

SraVaani-1.0 achieves the lowest word error rate (WER) on a large number of language-dataset pairs while remaining competitive with the best-performing systems on high resource while being assessed exclusively on the VAANI benchmark.

Sujith Pulikodan, A. Basu, J. PavanKumar et al. · 1 citation · ⚡1

Preprint Jul 2026

DONDO : Open w2v-BERT Speech-Recognition Base Models for African Languages Democratizing Oral Neural Dialect Ontology

We present DONDO, a family of open, permissively licensed automatic speech recognition (ASR) base models for African languages, built on the w2v-BERT 2.0 self-supervised speech encoder. DONDO comprises twenty-one monolingual models and five multilingual models spanning twenty-seven language varieties across Ghana, Sier...

P. Azunre, AI Khaya · 0 citations