Speech period detection using neural network classification

被引：0
|
作者：
Vrábel, A [1 ]
Rozinaj, G [1 ]
机构：
[1] Slovak Univ Technol Bratislava, FEEIT, Dept Telecommun, Bratislava 81219, Slovakia
来源：
IWSSIP 2005: PROCEEDINGS OF THE 12TH INTERNATIONAL WORSHOP ON SYSTEMS, SIGNALS & IMAGE PROCESSING | 2005年
关键词：
pitch detection; speech synthesis; neural network; EMU database system;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The implementation of the Slovak speech synthesizer, based on the TD PSOLA algorithm in the EMU database system [1], has proven the strong relation between accurate pitch period estimation and the quality of synthesized speech. Although the problem of pitch detection is well known for a long time, there has not been developed a method yet, which works well in general. In this work the neural network is used as a statistical classifier, generalizing outputs of various pitch detection algorithms. Further it describes its usage in the text-to-speech syn-thesizer and discusses achieved results.
引用
收藏
页码：145 / 148
页数：4
相关论文
共 50 条
  • [21] Multimodal speech emotion recognition and classification using convolutional neural network techniques
    Christy, A.
    Vaithyasubramanian, S.
    Jesudoss, A.
    Praveena, M. D. Anto
    INTERNATIONAL JOURNAL OF SPEECH TECHNOLOGY, 2020, 23 (02) : 381 - 388
  • [22] Multimodal speech emotion recognition and classification using convolutional neural network techniques
    A. Christy
    S. Vaithyasubramanian
    A. Jesudoss
    M. D. Anto Praveena
    International Journal of Speech Technology, 2020, 23 : 381 - 388
  • [23] Speech Sound Classification and Estimation of Optimal Order of LPC Using Neural Network
    Sankar, M. S. Arun
    Aiswariya, M.
    Rose, Dominic Anna
    Anushree, Bhat
    Shree, D. Bhagya
    Lakshmipriya, P. Mohan
    Sathidevi, P. S.
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON VISION, IMAGE AND SIGNAL PROCESSING (ICVISP 2018), 2018,
  • [24] A hybrid technique for speech segregation and classification using a sophisticated deep neural network
    Qazi, Khurram Ashfaq
    Nawaz, Tabassam
    Mehmood, Zahid
    Rashid, Muhammad
    Habib, Hafiz Adnan
    PLOS ONE, 2018, 13 (03):
  • [25] Speech-Act Classification Using Convolutional Neural Network and Word Embedding
    Bae, Kyoungman
    Ko, Youngjoong
    INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS, 2018, 27 (06)
  • [26] Analysis Text of Hate Speech Detection Using Recurrent Neural Network
    Saksesi, Arum Sucia
    Nasrun, Muhammad
    Setianingsih, Casi
    2018 INTERNATIONAL CONFERENCE ON CONTROL, ELECTRONICS, RENEWABLE ENERGY AND COMMUNICATIONS (ICCEREC), 2018, : 242 - 248
  • [27] Text Analysis For Hate Speech Detection Using Backpropagation Neural Network
    Setyadi, Nabiila Adani
    Nasrun, Muhammad
    Setianingsih, Casi
    2018 INTERNATIONAL CONFERENCE ON CONTROL, ELECTRONICS, RENEWABLE ENERGY AND COMMUNICATIONS (ICCEREC), 2018, : 159 - 165
  • [28] A Framework for Hate Speech Detection Using Deep Convolutional Neural Network
    Roy, Pradeep Kumar
    Tripathy, Asis Kumar
    Das, Tapan Kumar
    Gao, Xiao-Zhi
    IEEE ACCESS, 2020, 8 : 204951 - 204962
  • [29] Classification of the Period Undergraduate Study Using Back-propagation Neural Network
    Prasetyawan, Purwono
    Ahmad, Imam
    Borman, Rohmat Indra
    Ardiansyah
    Pahlevi, Yogi Aziz
    Kurniawan, Dwi Ely
    PROCEEDINGS OF THE 2018 INTERNATIONAL CONFERENCE ON APPLIED ENGINEERING (ICAE), 2018,
  • [30] Neural network classification and novelty detection
    Augusteijn, MF
    Folkert, BA
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2002, 23 (14) : 2891 - 2902
12345