FLEURS
Canonical54papers using it
2022first seen
FLEURS is a benchmark used to evaluate speech-to-text translation performance across multiple languages, including Central Kurdish.
Papers using FLEURS (53)
- Unified Model For Code-switching Speech Recognition And Language Identification Based On A Concatenated TokenizerSelf-supervised Adaptive Pre-training Of Multilingual Speech Models For Language And Dialect IdentificationFireRedASR2S: A State-of-the-Art Industrial-Grade All-in-One Automatic Speech Recognition SystemWhispering in Amharic: Fine-tuning Whisper for Low-resource LanguageA Compact End-to-end Model With Local And Global Context For Spoken Language IdentificationTowards 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 RecognitionDual-pipeline With Low-rank Adaptation For New Language Integration In Multilingual ASRCTC-GMM: CTC Guided Modality Matching For Fast And Accurate Streaming Speech TranslationSwedish Whispers; Leveraging a Massive Speech Corpus for Swedish Speech RecognitionEnglish 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 languagesMultilingual And Fully Non-autoregressive ASR With Large Language Model Fusion: A Comprehensive StudyInvestigating Decoder-only Large Language Models For Speech-to-text TranslationAfrica-centric Self-supervised Pre-training For Multilingual Speech Representation In A Sub-saharan ContextSeamlessM4T: Massively Multilingual & Multimodal Machine TranslationA 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 RefinementImproving Massively Multilingual ASR With Auxiliary CTC ObjectivesMultilingual and Fully Non-Autoregressive ASR with Large Language Model
Fusion: A Comprehensive StudyMaestro-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 LearningCTC-GMM: CTC guided modality matching for fast and accurate streaming
speech translationDENOASR: Debiasing ASRs through Selective DenoisingWhisper Finetuning on Nepali Language