Phoneme Segmentation using Deep Learning for Speech Synthesis

被引：2

作者：

Lee, Young Han ^{[1
]}

Yang, Jong-Yeol ^{[1
]}

Cho, Choongsang ^{[1
]}

Jung, Hyedong ^{[1
]}

机构：

[1] Korea Elect Technol Inst, Artificial Intelligent Res Ctr, Seongnam, South Korea

来源：

PROCEEDINGS OF THE 2018 CONFERENCE ON RESEARCH IN ADAPTIVE AND CONVERGENT SYSTEMS (RACS 2018) | 2018年

关键词：

Phoneme segmentation; Speech synthesis; Deep learning;

D O I：

10.1145/3264746.3264801

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

In this paper, we propose the phoneme segmentation method, which is one of the basic module that consist unit-selection-based speech synthesis, using deep learning algorithm. To enhance this, we apply the additional cross entropy loss into the Deep speech based speech recognition architecture. From this approach, we can get higher accuracy of phoneme boundary. In our experiments, the proposed method has 20.91 % boundary accuracy which is higher than the conventional phoneme segmentation.

引用

页码：59 / 61

页数：3

共 50 条

[21] Speech Recognition using Deep Learning
Lakkhanawannakun, Phoemporn
Noyunsan, Chaluemwut
2019 34TH INTERNATIONAL TECHNICAL CONFERENCE ON CIRCUITS/SYSTEMS, COMPUTERS AND COMMUNICATIONS (ITC-CSCC 2019), 2019, : 514 - 517
[22] Speech Separation Using Deep Learning
Nandal, P.
SUSTAINABLE COMMUNICATION NETWORKS AND APPLICATION, ICSCN 2019, 2020, 39 : 319 - 326
[23] Improving phoneme recognition of throat microphone speech recordings using transfer learning
Turan, M. A. Tugtekin
Erzin, Engin
SPEECH COMMUNICATION, 2021, 129 : 25 - 32
[24] COMPOSITE PHONEME UNITS FOR THE SPEECH SYNTHESIS OF JAPANESE
SAGISAKA, Y
SATO, H
SPEECH COMMUNICATION, 1986, 5 (02) : 217 - 223
[25] A Review of Deep Learning Based Speech Synthesis
Ning, Yishuang
He, Sheng
Wu, Zhiyong
Xing, Chunxiao
Zhang, Liang-Jie
APPLIED SCIENCES-BASEL, 2019, 9 (19):
[26] PHONEME POWER-CONTROL FOR SPEECH SYNTHESIS
ITOH, K
HIROKAWA, T
SATO, H
IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, 1993, E76A (11) : 1911 - 1918
[27] Stochastic Filter Approaches for a Phoneme-Based Segmentation of Speech Signals
Rauh, Andreas
Tiede, Susann
Klenke, Cornelia
2016 21ST INTERNATIONAL CONFERENCE ON METHODS AND MODELS IN AUTOMATION AND ROBOTICS (MMAR), 2016, : 732 - 737
[28] Text-Independent Phoneme Segmentation Combining EGG and Speech Data
Chen, Lijiang
Mao, Xia
Yan, Hong
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2016, 24 (06) : 1029 - 1037
[29] A neural speech decoding framework leveraging deep learning and speech synthesis
Chen, Xupeng
Wang, Ran
Khalilian-Gourtani, Amirhossein
Yu, Leyao
Dugan, Patricia
Friedman, Daniel
Doyle, Werner
Devinsky, Orrin
Wang, Yao
Flinker, Adeen
NATURE MACHINE INTELLIGENCE, 2024, 6 (04) : 467 - 480
[30] Phoneme recognition using speech image (spectrogram)
Ahmadi, M
Bailey, NJ
Hoyle, BS
ICSP '96 - 1996 3RD INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, PROCEEDINGS, VOLS I AND II, 1996, : 675 - 677

← 1 2 3 4 5 →