Automatic speech recognition of multiple accented English data
Dimitra Vergyri, Lori F Lamel, Jean‐Luc Gauvain · 2010
Accent variability is an important factor in speech that can sig-nificantly degrade automatic speech recognition performance. We investigate the effect of multiple accents on an English broadcast news recognition system. A multi-accented English corpus is used for the task, including broadcast news segments from 6 different geographic regions: US, Great Britain, Aus-tralia, North Africa, Middle East and India. There is signifi-cant performance degradation of a baseline system trained on only US data when confronted with shows from other regions. The results improve significantly when data from all the regions are included for accent-independent acoustic model training. Further improvements are achieved when MAP-adapted accent-dependent models are used in conjunction with a GMM accent classifier. Index Terms: accented speech recognition, accent adaptation 1.