학술논문
Context Tree Weighting을 이용한 AMR 음성 데이터 압축 성능 개선
Improvement of AMR Data Compression Using the Context Tree Weighting Method
Improvement of AMR Data Compression Using the Context Tree Weighting Method
Document Type
Article
Source
인터넷정보학회논문지 / Journal of Internet Computing and Services (JICS). Aug 30, 2020 21(4):35
Subject
Language
Korean
English
English
ISSN
1598-0170
Abstract
본 논문은 Context Tree Weighting (CTW) 를 이용하여 Adaptive Multi-Rate (AMR) 데이터의 압축 성능을 개선하는 알고리즘을 제안한다. AMR은 IMT-2000에서 채택된 음성부호화 표준안으로써, 무선채널의 환경변화에 대처할 수 있도록 4.75 kbit/s 에서 12.2 kbit/s 까지 8가지의 전송률을 지원한다. CTW는 산술부호화기의 일종으로, 가변 차수 마르코프 모델을 사용하는 압축기이다. 우리는 CTW가 비트단위로 수행한다는 점을 고려하여 AMR 데이터를 변환한 후 CTW로 압축하는 알고리즘을 제안한다. 제안하는 알고리즘의 유효성을 검증하기 위하여 ZIP을 포함한 기존 압축방식과 제안된 알고리즘의 압축률을 비교하는 실험을 하였다. 실험 결과, AMR 데이터의 평균 추가 압축률이 ZIP의 경우 약 3.21%, 제안된 알고리즘의 경우 약 9.10%로 나타났다. 따라서 본 논문에서 제안한 알고리즘이 AMR 데이터의 압축 성능을 약 5.89% 개선하였다.
This paper proposes an algorithm to improve the compression performance of the adaptive multi-rate (AMR) speech coding using the context tree weighting (CTW) method. AMR is the voice encoding standard adopted by IMT-2000, and supports 8 transmission rates from 4.75 kbit/s to 12.2 kbit/s to cope with changes in the channel condition. CTW as a kind of the arithmetic coding, uses a variable-order Markov model. Considering that CTW operates bit by bit, we propose an algorithm that re-orders AMR data and compresses them with CTW. To verify the validity of the proposed algorithm, an experiment is conducted to compare the proposed algorithm with existing compression methods including ZIP in terms of compression ratio. Experimental results indicate that the average additional compression rate in AMR data is about 3.21% with ZIP and about 9.10% with the proposed algorithm. Thus our algorithm improves the compression performance of AMR data by about 5.89%.
This paper proposes an algorithm to improve the compression performance of the adaptive multi-rate (AMR) speech coding using the context tree weighting (CTW) method. AMR is the voice encoding standard adopted by IMT-2000, and supports 8 transmission rates from 4.75 kbit/s to 12.2 kbit/s to cope with changes in the channel condition. CTW as a kind of the arithmetic coding, uses a variable-order Markov model. Considering that CTW operates bit by bit, we propose an algorithm that re-orders AMR data and compresses them with CTW. To verify the validity of the proposed algorithm, an experiment is conducted to compare the proposed algorithm with existing compression methods including ZIP in terms of compression ratio. Experimental results indicate that the average additional compression rate in AMR data is about 3.21% with ZIP and about 9.10% with the proposed algorithm. Thus our algorithm improves the compression performance of AMR data by about 5.89%.