FLEURS
Canonical52papers using it
2022first seen
FLEURS is a benchmark used to evaluate speech-to-text translation performance across multiple languages, including the assessment of translation quality in the context of the KUTED dataset for Central Kurdish.
Papers using FLEURS (52)
- FireRedASR2S: A State-of-the-Art Industrial-Grade All-in-One Automatic Speech Recognition SystemWhispering in Amharic: Fine-tuning Whisper for Low-resource LanguageTowards Inclusive ASR: Investigating Voice Conversion for Dysarthric Speech Recognition in Low-Resource LanguagesLanguage-Aware Prompt Tuning for Parameter-Efficient Seamless Language Expansion in Multilingual ASRBandwidth-Efficient and Privacy-Preserving Edge-Cloud Many-to-Many Speech TranslationUsing Songs to Improve Kazakh Automatic Speech RecognitionSwedish Whispers; Leveraging a Massive Speech Corpus for Swedish Speech RecognitionSN-WER: Script-Normalized WER for Multi-Script Indic ASR EvaluationBenchmarking Speech-to-Speech Translation ModelsA Comparative Study of Pre-trained Speech Encoders and Training Objectives for Large-Scale Indic Spoken Language IdentificationPiDA: Phonetically-Informed Data Augmentation for Robust Vietnamese Speech TranslationSometin Beta Pass Notin (SBPN): Improving Multilingual ASR for Nigerian Languages via Knowledge DistillationEnglish to Central Kurdish Speech Translation: Corpus Creation, Evaluation, and Orthographic StandardizationScript Collapse in Multilingual ASR: Defining and Measuring Script Fidelity RateVietSuperSpeech: A Large-Scale Vietnamese Conversational Speech Dataset for ASR Fine-Tuning in Chatbot, Customer Support, and Call Center ApplicationsTwo-Stage Adaptation for Non-Normative Speech Recognition: Revisiting Speaker-Independent Initialization for PersonalizationFLEURS-Kobani: Extending the FLEURS Dataset for Northern KurdishMCAT: Scaling Many-to-Many Speech-to-Text Translation with MLLMs to 70 LanguagesPOTSA: A Cross-Lingual Speech Alignment Framework for Speech-to-Text TranslationPART: Progressive Alignment Representation Training for Multilingual Speech-To-Text with LLMsDQLoRA: A Lightweight Domain-Aware Denoising ASR via Adapter-guided DistillationTraining-Free Voice Conversion with Factorized Optimal TransportImproving Language and Modality Transfer in Translation by Character-level ModelingOn the use of Performer and Agent Attention for Spoken Language
IdentificationAfriHuBERT: A self-supervised speech representation model for African languagesScaling Speech Technology to 1,000+ LanguagesImproving Massively Multilingual ASR With Auxiliary CTC ObjectivesFLEURS: Few-shot Learning Evaluation of Universal Representations of
SpeechSeamlessM4T: Massively Multilingual & Multimodal Machine TranslationMultilingual and Fully Non-Autoregressive ASR with Large Language Model
Fusion: A Comprehensive StudyA Compact End-to-End Model with Local and Global Context for Spoken
Language IdentificationSpeechMatrix: A Large-Scale Mined Corpus of Multilingual
Speech-to-Speech TranslationsGigaSpeech 2: An Evolving, Large-Scale and Multi-domain ASR Corpus for Low-Resource Languages with Automated Crawling, Transcription and RefinementCTC-GMM: CTC guided modality matching for fast and accurate streaming
speech translationMaestro-U: Leveraging joint speech-text representation learning for zero
supervised speech ASRLabel Aware Speech Representation Learning For Language IdentificationUnified model for code-switching speech recognition and language
identification based on a concatenated tokenizerHK-LegiCoST: Leveraging Non-Verbatim Transcripts for Speech TranslationSelf-supervised Adaptive Pre-training of Multilingual Speech Models for
Language and Dialect IdentificationWhispering in Norwegian: Navigating Orthographic and Dialectic
ChallengesGenTranslate: Large Language Models are Generative Multilingual Speech
and Machine TranslatorsAfrica-Centric Self-Supervised Pre-Training for Multilingual Speech
Representation in a Sub-Saharan ContextASTRA: Aligning Speech and Text Representations for Asr without SamplingDual-Pipeline with Low-Rank Adaptation for New Language Integration in
Multilingual ASRInvestigating Decoder-only Large Language Models for Speech-to-text
TranslationFLEURS-R: A Restored Multilingual Speech Corpus for Generation TasksASR Benchmarking: Need for a More Representative Conversational DatasetEMMeTT: Efficient Multimodal Machine Translation TrainingImproving Multilingual ASR in the Wild Using Simple N-best Re-rankingMaking LLMs Better Many-to-Many Speech-to-Text Translators with Curriculum LearningDENOASR: Debiasing ASRs through Selective DenoisingWhisper Finetuning on Nepali Language