This study examines strategies in responding to thanks by CanE （Canadian English） and CamE （Cameroon English） speakers. Based on data collected by means of a DCT （Discourse Completion Task） questionnaire, the st...This study examines strategies in responding to thanks by CanE （Canadian English） and CamE （Cameroon English） speakers. Based on data collected by means of a DCT （Discourse Completion Task） questionnaire, the study addresses formal, functional, situational, and interactional similarities and differences in both varieties of English. With regard to speaker strategies （Aijmer, 1996） or conventions of means, it was found that the Canadian participants mostly prefer ＂minimizing the favor＂ when responding to thanks, while the Cameroonians most frequently ＂express appreciation＂. At the level of the realization types, the findings show that patterns with ＂no problem＂ are predominant in the Canadian corpus, whereas the Cameroonian respondents rather employ patterns with ＂welcome＂. Differences can also be found in the situational distribution of the speaker strategies and their linguistic realizations as well as in the use and the length of supportive moves.展开更多
This letter proposes an effective and robust speech feature extraction method based on statistical analysis of Pitch Frequency Distributions (PFD) for speaker identification. Compared with the conventional cepstrum, P...This letter proposes an effective and robust speech feature extraction method based on statistical analysis of Pitch Frequency Distributions (PFD) for speaker identification. Compared with the conventional cepstrum, PFD is relatively insensitive to Additive White Gaussian Noise (AWGN), but it does not show good performance for speaker identification, even if under clean environments. To compensate this shortcoming, PFD and conventional cepstrum are combined to make the ultimate decision, instead of simply taking one kind of features into account.Experimental results indicate that the hybrid approach can give outstanding improvement for text-independent speaker identification under noisy environments corrupted by AWGN.展开更多
文摘This study examines strategies in responding to thanks by CanE （Canadian English） and CamE （Cameroon English） speakers. Based on data collected by means of a DCT （Discourse Completion Task） questionnaire, the study addresses formal, functional, situational, and interactional similarities and differences in both varieties of English. With regard to speaker strategies （Aijmer, 1996） or conventions of means, it was found that the Canadian participants mostly prefer ＂minimizing the favor＂ when responding to thanks, while the Cameroonians most frequently ＂express appreciation＂. At the level of the realization types, the findings show that patterns with ＂no problem＂ are predominant in the Canadian corpus, whereas the Cameroonian respondents rather employ patterns with ＂welcome＂. Differences can also be found in the situational distribution of the speaker strategies and their linguistic realizations as well as in the use and the length of supportive moves.
文摘This letter proposes an effective and robust speech feature extraction method based on statistical analysis of Pitch Frequency Distributions (PFD) for speaker identification. Compared with the conventional cepstrum, PFD is relatively insensitive to Additive White Gaussian Noise (AWGN), but it does not show good performance for speaker identification, even if under clean environments. To compensate this shortcoming, PFD and conventional cepstrum are combined to make the ultimate decision, instead of simply taking one kind of features into account.Experimental results indicate that the hybrid approach can give outstanding improvement for text-independent speaker identification under noisy environments corrupted by AWGN.
