Data Collection for Cross-lingual Speech Studies
In a significant stride for speech research, Facebook AI has unveiled the Multilingual LibriSpeech (MLS) dataset. This extensive audio dataset, credited to Mahesh Patel, is designed to aid in the development and comparison of speech recognition systems, with the ultimate goal of improving AI-powered services such as voice assistants.
MLS expands upon the English-only audiobook data from LibriVox, providing data for language-model training sets and pretrained language models across seven languages: German, Dutch, French, Spanish, Italian, Portuguese, and Polish. The dataset includes over 50,000 hours of audio, offering a comprehensive resource for researchers worldwide.
The Multilingual LibriSpeech dataset is a valuable tool for enabling researchers to compare existing data on different automatic speech recognition systems. By providing a multilingual dataset, MLS offers a unique opportunity to investigate the performance of various systems across multiple languages, fostering a more inclusive and versatile AI landscape.
Beyond improving voice assistants, MLS has potential applications beyond its initial intended purpose. As researchers delve deeper into the dataset, they may uncover insights that can be applied to other AI-powered services, such as language translation, speech synthesis, and more.
Mahesh Patel, the credit holder for the associated image, shared his thoughts on the significance of MLS for AI research, stating, "The Multilingual LibriSpeech dataset represents a monumental step forward in speech research, breaking down language barriers and paving the way for more inclusive AI-powered services."
Interested researchers can download the Multilingual LibriSpeech dataset from the official OpenSLR website (Open Speech and Language Resources). As the research community continues to explore the dataset's potential, we can expect to see advancements in speech recognition and AI technology that cater to a diverse and multilingual world.
