SPE-2: Speech Recognition 2: Neural transducer Models 2 |
Session Type: Poster |
Time: Tuesday, 8 June, 13:00 - 13:45 |
Location: Gather.Town |
Virtual Session: View on Virtual Platform |
Session Chair: Tara Sainath, Google Inc. |
SPE-2.1: ADVANCING RNN TRANSDUCER TECHNOLOGY FOR SPEECH RECOGNITION |
George Saon; IBM Research AI |
Zoltan Tueske; IBM Research AI |
Daniel Bolanos; IBM Research AI |
Brian Kingsbury; IBM Research AI |
SPE-2.2: LESS IS MORE: IMPROVED RNN-T DECODING USING LIMITED LABEL CONTEXT AND PATH MERGING |
Rohit Prabhavalkar; Google |
Yanzhang He; Google |
David Rybach; Google |
Sean Campbell; Google |
Arun Narayanan; Google |
Trevor Strohman; Google |
Tara N. Sainath; Google |
SPE-2.3: SIMPLEFLAT: A SIMPLE WHOLE-NETWORK PRE-TRAINING APPROACH FOR RNN TRANSDUCER-BASED END-TO-END SPEECH RECOGNITION |
Takafumi Moriya; NTT Corporation |
Takanori Ashihara; NTT Corporation |
Tomohiro Tanaka; NTT Corporation |
Tsubasa Ochiai; NTT Corporation |
Hiroshi Sato; NTT Corporation |
Atsushi Ando; NTT Corporation |
Yusuke Ijima; NTT Corporation |
Ryo Masumura; NTT Corporation |
Yusuke Shinohara; NTT Corporation |
SPE-2.4: ECHO STATE SPEECH RECOGNITION |
Harsh Shrivastava; Georgia Institute of Technology |
Ankush Garg; Google |
Yuan Cao; Google |
Yu Zhang; Google |
Tara N. Sainath; Google |
SPE-2.5: USING SYNTHETIC AUDIO TO IMPROVE THE RECOGNITION OF OUT-OF-VOCABULARY WORDS IN END-TO-END ASR SYSTEMS |
Xianrui Zheng; University of Cambridge |
Yulan Liu; Amazon |
Deniz Gunceler; Amazon |
Daniel Willett; Amazon |