2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
Login Paper Search My Schedule Paper Index Help

My ICASSP 2021 Schedule

Note: Your custom schedule will not be saved unless you create a new account or login to an existing account.
  1. Create a login based on your email (takes less than one minute)
  2. Perform 'Paper Search'
  3. Select papers that you desire to save in your personalized schedule
  4. Click on 'My Schedule' to see the current list of selected papers
  5. Click on 'Printable Version' to create a separate window suitable for printing (the header and menu will appear, but will not actually print)

Paper Detail

Paper IDSPE-46.3
Paper Title MULTILINGUAL PHONETIC DATASET FOR LOW RESOURCE SPEECH RECOGNITION
Authors Xinjian Li, David Mortensen, Florian Metze, Alan Black, Carnegie Mellon University, United States
SessionSPE-46: Corpora and Other Resources
LocationGather.Town
Session Time:Thursday, 10 June, 16:30 - 17:15
Presentation Time:Thursday, 10 June, 16:30 - 17:15
Presentation Poster
Topic Speech Processing: [SPE-GASR] General Topics in Speech Recognition
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Phone Recognition is one of the most important tasks in the field of multilingual speech recognition, especially for low-resource languages whose orthographies are not available. However, most speech recognition datasets so far only focus on high-resource languages, there are very few datasets available for low-resource languages, especially datasets with detailed phone annotation. In this work, we present a large multilingual phonetic dataset, which is preprocessed and aligned from the UCLA phonetic dataset. The dataset contains around 100 low-resource languages and 7000 utterances in total. This dataset would provide an ideal training/evaluation set for universal phone recognition.