Refinement of Landmark Detection and Extraction of Articulator-Free Features for Knowledge-Based Speech Recognition

Jung-In LEE; Jeung-Yoon CHOI; Hong-Goo KANG

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Refinement of Landmark Detection and Extraction of Articulator-Free Features for Knowledge-Based Speech Recognition

机译：精炼地标检测和无发音器特征提取，用于基于知识的语音识别

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摘要

Refinement methods for landmark detection and extraction of articulator-free features for a knowledge-based speech recognition system are described. Sub-band energy difference profiles are used to detect landmarks, with additional parameters used to improve accuracy. For articulator-free feature extraction, duration, relative energy, and silence detection are additionally used to find [continuant] and [strident] features. Vowel, obstruent and sonorant consonant landmarks, and locations of voicing onsets and offsets are detected within a unified framework with 85% accuracy overall. Additionally, 75% and 79% of [continuant] and [strident] features, respectively, are detected from landmarks.

机译：描述了用于基于知识的语音识别系统的界标检测和无咬合器特征提取的改进方法。子带能量差异曲线用于检测界标，并使用附加参数来提高准确性。对于无咬合器的特征提取，还需要使用持续时间，相对能量和静默检测来发现[连续]和[尖峰]特征。在统一的框架内可以检测出元音，晦涩和发声的辅音界标以及发声开始和偏移的位置，总体准确度为85％。此外，从地标中分别检测到[连续]和[显着]特征的75％和79％。

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来源
《IEICE Transactions on Information and Systems》 |2013年第3期|746-749|共4页
作者
Jung-In LEE; Jeung-Yoon CHOI; Hong-Goo KANG;
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作者单位

The authors are with Electrical and Electronic Engineering,Yonsei University, 134 Shinchon-dong Seodaemoon-gu, 120-749 Seoul Korea;

The authors are with Electrical and Electronic Engineering,Yonsei University, 134 Shinchon-dong Seodaemoon-gu, 120-749 Seoul Korea;

The authors are with Electrical and Electronic Engineering,Yonsei University, 134 Shinchon-dong Seodaemoon-gu, 120-749 Seoul Korea;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类
关键词
speech recognition; acoustic events; landmark detection;

机译：语音识别;声音事件;界标检测;

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专利

1. Refinement of Landmark Detection and Extraction of Articulator-Free Features for Knowledge-Based Speech Recognition [J] . Jung-In LEE, Jeung-Yoon CHOI, Hong-Goo KANG IEICE transactions on information and systems . 2013,第3期

机译：改进地标检测和无发音器特征提取，用于基于知识的语音识别
2. A probabilistic framework for landmark detection based on phonetic features for automatic speech recognition [J] . Juneja A, Espy-Wilson C The Journal of the Acoustical Society of America . 2008,第2期

机译：基于语音特征的地标检测概率框架，用于自动语音识别
3. Facial Expression Recognition using Facial Landmark Detection and Feature Extraction on Neural Networks [J] . Fuzail Khan International Journal of Applied Engineering Research . 2018,第20aPta2期

机译：使用面部地标检测和神经网络特征提取的面部表情识别
4. Application of EαNets to Feature Recognition of Articulation Manner in Knowledge-Based Automatic Speech Recognition [C] . Sabato M. Siniscalchi, Jinyu Li, Giovanni Pilato, Italian Workshop on Neural Nets . 2006

机译：Eαnets在知识自动语音识别中的特征识别特征识别
5. Speech recognition based on phonetic features and acoustic landmarks. [D] . Juneja, Amit. 2004

机译：基于语音特征和声学界标的语音识别。
6. On the Speech Properties and Feature Extraction Methods in Speech Emotion Recognition [O] . Juraj Kacur, Boris Puterka, Jarmila Pavlovicova, 2021

机译：语音情感识别中的语音特性和特征提取方法
7. Landmark detection for distinctive feature-based speech recognition. [O] . Liu, Sharlene Anne 1995

机译：基于特征的语音识别的地标检测。

Refinement of Landmark Detection and Extraction of Articulator-Free Features for Knowledge-Based Speech Recognition

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