Papers by Hiroshi Seki
A Purely End-to-End System for Multi-speaker Speech Recognition (P18-1)
Copied to clipboard
| Challenge: | Existing methods for multi-speaker speech recognition require isolated source signals or senone alignments for effective learning. |
| Approach: | They propose a sequence-to-sequence framework to decode multiple label sequences from a single speech sequence by unifying source separation and speech recognition functions in an end-to end manner. |
| Outcome: | The proposed model improves on existing models by 83.1% relative to previous models with explicit separation and recognition modules. |