arXiv:2609.36920v1 Announce Type: new
Abstract: Comprehensive evaluations of automatic speech recognition (ASR) for Iberian languages remain limited, and low-resource languages, biases, and efficienc...
By Fernando L\'opez, Pablo G\'omez, David Solans, Paulo Villegas, Jordi Luque
The study fine‑tunes the Whisper Small model for Automatic Speech Recognition (ASR) in Baniwa, an indigenous Arawakan language. Using a 0.54‑hour corpus of 1,373 manually transcribed recordings, the fine‑tuned model achieved a Word Error Rate of 37.5% and a Character Error Rate of 7.45%. These results provide an initial baseline for Baniwa ASR and suggest that multilingual foundation models can be adapted to extremely low‑resource languages.
By Leonardo Duart, Tiago Fonseca, Thiago Chac\'on
arXiv:2608. 19361v1 Announce Type: new Abstract: This study reports the development of an Automatic Speech Recognition (ASR) system in Mizo, a low-resource language.
By Priyankoo Sarmah, Sanasam Ranbir Singh, Lalhmingmawia
arXiv:2508. 05149v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated potential in handling spoken inputs for high-resource languages, reaching state-of-the-art performance in various tasks.
By Seraphina Fong, Marco Matassoni, Alessio Brutti
Nord-Parl-TTS is an open text‑to‑speech dataset for Finnish and Swedish created from recordings of Nordic parliamentary proceedings. It contains 900 hours of Finnish and 5 090 hours of Swedish speech, processed with an adapted Emilia pipeline and accompanied by unified evaluation sets for model development and benchmarking. The dataset aims to reduce the resource gap in TTS between high‑ and lower‑resourced languages.
By Zirui Li, Jens Edlund, Yicheng Gu, Nhan Phan, Lauri Juvela, Mikko Kurimo
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