Abstract When linguists, psychologists or engineers try to understand, explain or imitate human speech and language, they usually do so by modeling individual speakers, hearers or learners. Nevertheless, language is an emergent property of groups[…]
Abstract The talk describes our work towards data-driven features that could be used with the current HMM system and that would represent transformed posterior probabilities of the sub-word classes. To address steady or slowly-varying artifacts,[…]
Abstract Event extraction involves automatically finding, within a text, instances of a specified type of event, and filling a data base with information about the participants and circumstances (date, place) of the event. These data[…]
Abstract This talk introduces a new covariance modeling technique for Gaussian Mixture Models. Specifically the inverse covariance (precision) matrix of each Gaussian is expanded in a rank-1 basis. A generalized EM algorithm is proposed to[…]
Abstract Speech technology (including synthesis, speech recognition and speaker verification) has made significant advances in recent years in laboratories and in field applications, but speech recognition can still degrade when the test data do not[…]
Abstract It is often claimed that irregular verbs in English are learned by memorizing associated pairs between stems and past tense forms, and hence, that frequency of an irregular verb largely determines the success of[…]
