Language accent classification in American English
Speech Communication
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Frequency Characteristics of Foreign Accented Speech
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 2 - Volume 2
Automatic dialect identification of extemporaneous conversational, Latin American Spanish speech
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02
Fast accent identification and accented speech recognition
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
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In forensic investigations, it would be helpful to be able to identify a speaker's native language based on the sound of their speech. Previous research on foreign accent identification suggested that the identification accuracy can be improved by using linguistic forms in which non-native characteristics are reflected. This study investigates how native and non-native speakers of Japanese differ in reading Japanese telephone numbers, which have a specific prosodic structure called a bipodic template. Spoken Japanese telephone numbers were recorded from native speakers, and Chinese and Korean learners of Japanese. Twelve utterances were obtained from each speaker, and their F0 contours were compared between native and non-native speakers. All native speakers realised the prosodic pattern of the bipodic template while reading the telephone numbers, whereas non-native speakers did not. The metric rhythm and segmental properties of the speech samples were also analysed, and a foreign accent identification experiment was carried out using six acoustic features. By applying a logistic regression analysis, this method yielded an 81.8% correct identification rate, which is slightly better than that achieved in other studies. Discrimination accuracy between native and non-native accents was better than 90%, although discrimination between the two non-native accents was not that successful. A perceptual accent identification experiment was also conducted in order to compare automatic and human identifications. The results revealed that human listeners could discriminate between native and non-native speakers better, while they were inferior at identifying foreign accents.