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FLEURS-R: A Restored Multilingual Speech Corpus for Generation Tasks

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arxiv 2408.06227 v1 pith:H3KU4EAS submitted 2024-08-12 cs.CL cs.AIcs.SDeess.AS

FLEURS-R: A Restored Multilingual Speech Corpus for Generation Tasks

Min Ma , Yuma Koizumi , Shigeki Karita , Heiga Zen , Jason Riesa , Haruko Ishikawa , Michiel Bacchiani This is my paper
classification cs.CL cs.AIcs.SDeess.AS
keywords speechcorpusfleurs-rlanguagesfleursgenerationimprovedquality
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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This paper introduces FLEURS-R, a speech restoration applied version of the Few-shot Learning Evaluation of Universal Representations of Speech (FLEURS) corpus. FLEURS-R maintains an N-way parallel speech corpus in 102 languages as FLEURS, with improved audio quality and fidelity by applying the speech restoration model Miipher. The aim of FLEURS-R is to advance speech technology in more languages and catalyze research including text-to-speech (TTS) and other speech generation tasks in low-resource languages. Comprehensive evaluations with the restored speech and TTS baseline models trained from the new corpus show that the new corpus obtained significantly improved speech quality while maintaining the semantic contents of the speech. The corpus is publicly released via Hugging Face.

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  1. BlasBench: An Open Benchmark for Irish Speech Recognition

    cs.CL 2026-04 conditional novelty 6.0

    BlasBench supplies an Irish-aware normalizer and scoring harness that enables reproducible ASR comparisons and exposes a 33-43 point generalization gap for fine-tuned models versus 7-10 points for massively multilingual ones.