Fundamentals of speech recognition
Fundamentals of speech recognition
Machine Learning
MAP estimation of continuous density HMM: theory and applications
HLT '91 Proceedings of the workshop on Speech and Natural Language
The design for the wall street journal-based CSR corpus
HLT '91 Proceedings of the workshop on Speech and Natural Language
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
An overview of text-independent speaker recognition: From features to supervectors
Speech Communication
Advances in phone-based modeling for automatic accent classification
IEEE Transactions on Audio, Speech, and Language Processing
Unsupervised Discriminative Training With Application to Dialect Classification
IEEE Transactions on Audio, Speech, and Language Processing
Characterizing phonetic transformations and fine-grained acoustic differences across dialects
Characterizing phonetic transformations and fine-grained acoustic differences across dialects
Hi-index | 0.00 |
In this work, we propose a framework that automatically discovers dialect-specific phonetic rules. These rules characterize when certain phonetic or acoustic transformations occur across dialects. To explicitly characterize these dialect-specific rules, we adapt the conventional hidden Markov model to handle insertion and deletion transformations. The proposed framework is able to convert pronunciation of one dialect to another using learned rules, recognize dialects using learned rules, retrieve dialect-specific regions, and refine linguistic rules. Potential applications of our proposed framework include computer-assisted language learning, sociolinguistics, and diagnosis tools for phonological disorders.