arXiv AI June 30, 2026 By Kush Juvekar, Kavya Manohar, Aditya Srinivas Menon, Arghya Bhattacharya, Kumarmanas Nethil

Vividh-ASR: A Complexity-Tiered Benchmark and Optimization Dynamics for Robust Indic Speech Recognition

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.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv AI

Aug 14

Comparative Analysis of Multilingual Pre-trained Models for Nepali Automatic Speech Recognition

arXiv:2608. 12327v1 Announce Type: cross Abstract: Multilingual pretrained models nominally support Nepali, yet no controlled benchmark has compared them under a single fine-tuning protocol.

By Suman Paudel, Sarbin Sayami

fine-tuning multimodal benchmarks

arXiv AI

Jul 28

Indic DiarBench: A Multilingual Joint Diarization and ASR Benchmark for Indian Languages

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

llms multimodal benchmarks

arXiv Machine Learning

Jul 21

Robust Assamese Speech Recognition through Controlled Fine-Tuning of Whisper Models

arXiv:2607. 17164v1 Announce Type: new Abstract: Developing Automatic Speech Recognition (ASR) for morphologically rich, low-resource languages such as Assamese is challenging due to insufficient annotated speech data.

By Ganapati Das, Dwipen Laskar, Hasin Afzal Ahmed, Sanjib Kr Kalita, Kshirod Sarmah, Hem Chandra Das, Manjula Kalita

fine-tuning multimodal safety

arXiv Computation and Language

Sep 22

Federated Multilingual Speech-LLMs: Architecture and Aggregation Strategy Benchmarking

arXiv:2609.23825v1 Announce Type: new Abstract: We present a comprehensive benchmark of Federated Learning (FL) for multilingual Automatic Speech Recognition (ASR), evaluating four Speech-LLM archite...

By Jordi Luque, Aleix Sant, Fernando L\'opez

llms fine-tuning multimodal benchmarks safety

arXiv AI

Jul 15

Audio-Native Speech Recognition with a Frozen Discrete-Diffusion Language Model

arXiv:2607. 13013v1 Announce Type: new Abstract: Automatic speech recognition is dominated by autoregressive decoders that emit one token at a time.

By Harsha Vardhan Khurdula, Abhinav Kumar Singh, Yoeven D Khemlani, Vineet Agarwal

llms rag diffusion multimodal

arXiv Computation and Language

Sep 22

Vimarsha: Faithful ASR Evaluation for Indian Languages with Demographic Diversity, In-the-Wild Audio and Spelling Variations

arXiv:2609.24199v1 Announce Type: new Abstract: Evaluation benchmarks for Indian language automatic speech recognition (ASR) suffer from two systematic biases: optimistic scores from clean, controlle...

By Kaushal Santosh Bhogale, Srija Anand, Sadakopa Ramakrishnan Thothathiri, Tahir Javed, Sshubam Verma, Mitesh M. Khapra

multimodal benchmarks

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Related stories

Comparative Analysis of Multilingual Pre-trained Models for Nepali Automatic Speech Recognition

Indic DiarBench: A Multilingual Joint Diarization and ASR Benchmark for Indian Languages

Robust Assamese Speech Recognition through Controlled Fine-Tuning of Whisper Models

Federated Multilingual Speech-LLMs: Architecture and Aggregation Strategy Benchmarking

Audio-Native Speech Recognition with a Frozen Discrete-Diffusion Language Model

Vimarsha: Faithful ASR Evaluation for Indian Languages with Demographic Diversity, In-the-Wild Audio and Spelling Variations