An approach to speaker identification using DP-matched LVQ neural networks.
スポンサーリンク
概要
- 論文の詳細を見る
Automatic speaker identification is the other aspect in speech science, vis-a-vis spoken word recognition. In its traditional realization as a pattern classification task, there are some difficulties, such as the uncertainty of personalities, the dynamic variation of features, and so on. Nevertheless, vector quantization based pattern classifier still gains remarkable interest, because of its simplicity and the recent development in parallel computation technology. There are several reports on the combination technique of LVQ and other method for improvement of the conventional classifier. However, this paper concentrates on a hybrid algorithm of LVQ and DP-matching. The feature normalization capability in both thetime and frequency domains of such a method can decrease the incorrect speaker identification which is caused by the variation of feature vectors in a short-term or a long-term. The experiment of 10 speakers identification shows that the proposed method can produce the better reference vectors, and hence it can promote the correct identification.
- 一般社団法人 日本音響学会の論文
一般社団法人 日本音響学会 | 論文
- How large is the individual difference in hearing sensitivity?: Establishment of ISO 28961 on the statistical distribution of hearing thresholds of otologically normal young persons
- Applying generation process model constraint to fundamental frequency contours generated by hidden-Markov-model-based speech synthesis
- Vocal cord vibration in the production of consonants. Observation by means of high-speed digital imaging using a fiberscope.:Observation by means of high-speed digital imaging using a fiberscope
- The early reflections of the impulse response in an auditorium.
- Multiple reflections between rigid plane panels.