arXiv:2012.03411
공식 코드 · Papers with Code
MLS: A Large-Scale Multilingual Dataset for Speech Research
원문 초록
This paper introduces Multilingual LibriSpeech (MLS) dataset, a large multilingual corpus suitable for speech research. The dataset is derived from read audiobooks from LibriVox and consists of 8 languages, including about 44.5K hours of English and a total of about 6K hours for other languages. Additionally, we provide Language Models (LM) and baseline Automatic Speech Recognition (ASR) models and for all the languages in our dataset. We believe such a large transcribed dataset will open new avenues in ASR and Text-To-Speech (TTS) research. The dataset will be made freely available for anyone at http://www.openslr.org.
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From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition
VITA-Audio: Fast Interleaved Cross-Modal Token Generation for Efficient Large Speech-Language Model
Voila: Voice-Language Foundation Models for Real-Time Autonomous Interaction and Voice Role-Play
NonverbalTTS: A Public English Corpus of Text-Aligned Nonverbal Vocalizations with Emotion Annotations for Text-to-Speech
LM-SPT: LM-Aligned Semantic Distillation for Speech Tokenization
Transcript-Prompted Whisper with Dictionary-Enhanced Decoding for Japanese Speech Annotation
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