Earticle

Audiovisual (AV) facilities such as TVs and signage are installed in various public places. However, audio cannot be used to prevent noise and interference from individuals, which results in a loss of concentration and understanding of AV content. To address this problem, a total technique for remotely listening to audio from audiovisual facilities with clean sound quality while maintaining video and lip-syncing through personal smart mobile devices is proposed in this paper. Through the experimental results, the proposed scheme has been verified to reduce system power consumption by 8% to 16% and provide real-time processing with a low latency of 120 ms. The system described in this paper will contribute to the activation of audio telehearing services as it is possible to provide audio remote services in various places, such as express buses, trains, wide-area and intercity buses, public waiting rooms, and various application services.

In digital forensics, timestamps are crucial for analyzing key events in chronological order, making them vital to forensic investigations. This paper presents a method for detecting attempts to conceal a crime through the manipulation of timestamps on IT devices. Specifically, we introduce a technique to identify timestamp manipulation in a car’s infotainment system when the suspect's smartphone is connected via Bluetooth. The method involves extracting and analyzing Bluetooth Host Controller Interface (HCI) logs, Bluetooth logs, and system logs from both the smartphone and the infotainment system. Scenario-based experiments demonstrate the effectiveness of this technique in detecting timestamp manipulation on the infotainment system.

Vehicles with an Audio-Video Navigation (AVN) system have become another source of potential digital evidence. The AVN systems in modern cars retain information and event data from mobile devices connected to the car’s infotainment module, and navigation data in the form of tracklogs. These data provide a time history of a car’s geolocation that may be used to investigate an incident involving an automobile or reconstruct a crash. There has been little research into what types of user artifacts can be found on the AVN systems, and whether the AVN systems provide more vehicle event information than the connected mobile devices. For this study, we used the AVN system of a KIA NIRO EV vehicle for digital data acquisition and analysis. We have found that the AVN system provided some amounts of user data (start log, favorite routes, last destination search history, etc.). The acquired data and analyzed results can serve as basic digital evidence for vehicle forensic research.

Recently autonomous vehicles and connected cars are being equipped with various information and communication technology (ICT). The installed ICT on such vehicles and cars makes it possible to record events generated during communication between the built-in ICT module and the driver’s mobile phones and driver’s activity information. For example, the Audio Video Navigation (AVN) system, an ICT module, interacts with drivers and provides convenient features to drivers. AVN can be connected to a driver’s mobile device, and it can be used to store various driver-specific real time information such as driving records, phone call records, SMS, and music playback events. In this paper, we collect and analyze the digital data stored in an AVN installed in a KIA K5 sedan. Most of the analyzed data is related to the activities initiated from the mobile device connected to the AVN via Bluetooth. The result of our research reported in this paper can be useful for the forensic data analysis of vehicles.

음원 서비스의 주요 기능 중 하나인 내용 기반 검색을 위해 음원의 지문을 채취하여 데이타베이스에 저장하고 색인하여 검색에 활용하는 기법이 널리 사용되고 있다. 그런데 지속적으로 추가되는 신규 음원의 지문이 기존의 데이타베이스에 계속 삽입되면 공간 효율 및 음원 검색 성능의 저하가 점차 초래되는 문제점이 있다. 따라서 시스템 운용 비용의 증가를 가져오는 주기적인 데이터 베이스 재구성 없이 효율적인 음원 데이타베이스의 확장을 지원하는 기법이 요구된다. 본 논문에서는 샤잠의 지문 채취 알고리즘을 기반으로 클러스터 컴퓨팅 환경에서 맵리듀스 및 NoSQL 데이타베이스를 사용하여 이러한 문제를 해결하는 내용 기반 음원 검색 시스템의 설계를 제시하고 실제 음원 데이터를 이용한 다양한 실험을 통해 그 성능을 평가한다.

For content-based audio retrieval which is one of main functions in audio service, the techniques for extracting fingerprints from the audio source, storing and indexing them in a database are widely used. However, if the fingerprints of new audio sources are continually inserted into the database, there is a problem that space efficiency as well as audio retrieval performance are gradually deteriorated. Therefore, there is a need for techniques to support efficient expansion of audio database without periodic reorganization of the database that would increase the system operation cost. In this paper, we design a content-based audio retrieval system that solves this problem by using MapReduce and NoSQL database in a cluster computing environment based on the Shazam's fingerprinting algorithm, and evaluate its performance through a detailed set of experiments using real world audio data.

본 논문에서는 인터넷 기반 스트리밍 음악 서비스의 저작권 보호를 위한 새로운 오디오 포렌식마킹 시스템을 제안한다. 제안한 방법에서는 스트리밍 서비스의 QoS 보장을 위해 고속으로 포렌식마크가 삽입된 MP3 파일을 생성한다. 이를 위하여 사전 포렌식마킹 과정을 두고, 사전 처리된 MP3 파일을 프레임 단위 조합 방식으로 사용자 정보가 삽입된 새로운 MP3 파일을 생성한다. 실험 결과, 제안한 방법은 강인성과 비인지성 및 실시간성 등에서 만족스러운 결과를 보였다. 또한 서버/클라이언트로 구현된 스트리밍 기반 오디오 포렌식마킹 시스템에서 실시간 삽입과 모바일 단말에서의 재생과 함께 삽입된 포렌식마크 검출이 가능함을 확인하였다.

In this paper, we propose a new audio forensic marking system for protecting the copyright of the Internet-based music streaming services. In the proposed method, in order to guarantee the QoS of the streaming service, high speed, and generates a forensic mark inserted MP3 file. We make pre-marking process and generate a new forensic marked MP3 file, a combination of the pre-marked MP3 frame, the inserted user information. Experimental results show that the proposed method satisfactory results robustness and imperceptibility, and real-time properties. In addition, we were confirmed that the real-time embedding and detection from the streaming-based audio forensic marking system that has been implemented on the server/client is possible.

본 논문은 자동차 오디오 시스템에 내장된 라디오에서 실시간으로 재생되는 연속적인 오디오 신호로부터 음악 신호를 선별하고, 해당 음악에 대한 실시간 음악장르 분류를 통해 자동으로 이퀄라이저를 조절하는 방식을 제안한다. 제안된 방식에서는 음악분류 정확도를 높이고 실시간 신호처리를 실행하기 위해 연속적인 오디오 신호로부터 추출한 음색 특징 벡터와 리듬 특징 벡터를 GMM (Gaussian mixture model) 분류 방식에 적용하여 음악 분류를 수행한다. 제안된 방식은 카 오디오 시스템의 라디오로부터 출력된 오디오 신호로부터 분할된 다양한 오디오 구간을 5가지 음악장르로 분류하여 음악 장르 분류 성능을 측정하였다.

This paper proposes an automatic equalizer control method in automobile audio system. The proposed method discriminates the music segment from the consecutive real-time audio stream of the radio and the equalizer is controlled automatically according to the classified genre of the music segment. For enhancing the accuracy of the music genre classification in real-time, timbre feature and rhythm feature extracted from the consecutive audio stream is applied to GMM(Gaussian mixture model) classifier. The proposed method evaluates the performance of the music genre classification, which classified various audio segments segmented from the audio signal of the radio broadcast in automobile audio system into one of five music genres.

국내에서의 공연실황 녹음은 스테레오 방식과 스폿 마이킹(spot-miking) 방식을 혼합한 방식으로 주로 이루어져왔으나 최 근에는 복수의 모노 마이크를 이용한 서라운드 마이크 어레이(Surround Microphone Array)나 “구”형태의 서라운드 마이크 와 휴대용 멀티 트랙 녹음기와 DAW(Digital Audio Workstation) 시스템을 조합하여 녹음 자체를 서라운드 포맷으로 녹음하 는 방식이 시도되고 있다. 서라운드 사운드가 가지고 있는 형식상의 장점은 잘 알려져 있으나 실제 공연실황 녹음을 서라운 드로 진행하고 스테레오 방식과 비교 청취하는 경우는 적었으며 본 연구를 통하여 녹음, 믹싱 및 비교청취를 함으로써 서라 운드 녹음의 장점을 확인할 수 있었다.

Stereo and spot-miking was a major recording method at concert hall. However, many types of surround recordings are tried recently. Combining a surround microphone array which is made of multiple mono microphones or a surround microphone and portable multi-track recorder or DAW(Digital Audio 'Workstation) system, more and more venues are recorded and mixed in surround sound system. The benefits of surround sound format are well known, however, not many surround recording were tried and analyzed before. Through this research, we have found that the advantage of surround recording and mixing over conventional stereo format.

본 논문은 화력 발전소 및 시멘트 산업에서 필요한 원자재의 운송 수단에 사용되는 컨베이어 시스템에서의 고장을 검출하는 방법을 제안하였다. 산업현장에서 사람이 접근하기가 힘들고 넓은 공간에 시스템이 동작 하는 점을 고려하여 소 형 드론을 설계하였고 컨베이어의 이상을 감지하기 위하여 컨베이어에 내장된 모터의 이상 소음을 감지하는 방법을 임베디 드 환경으로 설계하여 드론에 장착하는 구조로 제안하였다. 시스템을 임베디드 마이크로프로세서에 적용하기 위하여 제한 된 메모리와 수행 시간을 고려한 하드웨어 및 알고리즘을 제안하였으며 주파수 분석을 통해 고장의 경향을 파악하여 알고 리즘 화 하였다. 이때 고장 판별 방식은 측정을 통하여 피크주파수를 측정하고 고주파수의 연속성을 감지하는 방식으로 고장에 의한 소음의 높은 주파수를 분석하여 고장진단을 시행할 수 있었다. 제안된 시스템은 실제 화력 발전소에서 취득한 데이터를 바탕으로 실험 환경을 구성하였으며 드론에 설계된 시스템을 탑재하여 가상 환경 실험을 하여 제안된 시스템의 유용성을 확인하였다. 향후에는 드론의 비행 안정성 향상과 고장 주파수에 대한 좀 더 정밀한 방법을 사용하여 판별성능을 향상 시키는 연구가 요구된다.

This paper proposes a method for detecting faults in conveyor systems used for transportation of raw materials needed in the thermal power plant and cement industries. A small drone was designed in consideration of the difficulty in accessing the industrial site and the need to use it in wide industrial site. In order to apply the system to the embedded microprocessor, hardware and algorithms considering limited memory and execution time have been proposed. At this time, the failure determination method measures the peak frequency through the measurement, detects the continuity of the high frequency, and performs the failure diagnosis with the high frequency components of noise. The proposed system consists of experimental environment based on the data obtained from the actual thermal power plant, and it is confirmed that the proposed system is useful by conducting virtual environment experiments with the drone designed system. In the future, further research is needed to improve the drone's flight stability and to improve discrimination performance by using more intelligent methods of fault frequency.

Recently, audio systems are changing the configuration of conventional sound reinforcement (SR) systems and public address (PA) systems by using audio over IP (AoIP), a technology that can transmit and receive audio signals based on internet protocol (IP). With the advancement of IP technology, AoIP technologies are leading the audio market and various technologies are being released. In particular, audio networks and control hierarchy over peer-to-peer (Anchor) technology based on AoIP is a system that transmits and receives audio signals over a wide bandwidth without an audio mixer, creating a novel paradigm for existing audio system configurations. Anchor technology forms an audio system by connecting audio sources and output equipment with On-site audio center (OAC), a device that can transmit and receive IP. Anchor's receiving OAC is capable of receiving and mixing audio signals transmitted from different IPs, making it possible to configure a novel audio system by replacing the conventional audio mixer. However, Anchor technology does not have the ability to provide audio effects to input devices such as microphones and instruments in the audio system configuration. Due to this, when individual control of each audio source is required, there is a problem of not being able to control the input signal, and it is impossible to individually affect a specific input signal. In this paper, we implemented a tone control module that can individually control the tone of the audio source of the input device using the audio processor core in the audio system based on Anchor technology, tone control for audio sources is possible through a tone control module connected to the transmitting OAC. As a result of the study, we confirmed that OAC receives the signal from the audio source, adjusts the tone and outputs it on the tone control module. Based on this, it was possible to solve problems that occurred in Anchor technology through transmitting OAC and tone control modules. In the future, we hope that the audio system configuration using Anchor technology will become established as the standard for audio equipment.

Most significantly, user customized control for a sound of digital audio in a smart home must be able to adjust many environmental contexts simultaneously. A sound is affected by a temperature, humidity, and atmospheric pressure. And user must tune the sound of digital audio every time according to environmental contexts. In this paper, we developed a customized user interface for a remote control of digital audio in a smart home according to the environmental contexts. The kinds of input environmental contexts are a temperature, humidity, location, weather, and atmospheric pressure. It creates an experience especially for a user of digital audio sound, allowing the user to interact with the control for digital audio operation in a natural and intuitive way.

Digital audio is technology that can be used to record, store, generate, manipulate, and reproduce sound using audio signals encoded in digital form. A band-pass filter is a device that passes frequencies within a certain range and rejects (attenuates) frequencies outside that range. Graphic equalizers are often included in consumer audio equipment and software which plays music on home computers. In the graphic equalizer, the input signal is sent to a bank of filters. The digital audio system for concert in opera theater or concert hall must be installed a lot of speaker units. Also, the speaker units are installed at intervals in a theater. And the audio systems must be controlled by the kinds of concert for the best sound quality. As that result, the user needs the remote control in order to play the audio system according to the kinds of concert in opera theater or concert hall efficiently in real-time. In this paper, we implement the mobile application for the remote control using wireless communications to control the digital audio system. Also, we implement the crossover and equalizer of the digital audio system. Each GEQ (Graphic EQualizer) Vertical Seek Bar is used. It has the frequency range value from -15.0 to 15.0 and the frequency range value is divided in units of 0.5 such as -15.0, -14.5, -14.0 …. 14.0, 14.5, and 15. And the 31Vertical Seek Bars are used for controlling each frequency range of volume. Also they are represented by graphic user interface for easy operation of user.

Audio identification technologies are becoming of increasing interest for copyright protection and digital forensic. In this paper, we propose an audio fragment identification system for efficient audio identifying applications in practice. To identify an audio file fragment, we have to decode it according to its format. Thus, we precede format classification of audio fragment using Support Vector Machine in advance. After identify the format, fragment recovery is implemented by adding a maximum similar frame header in front of the fragment. Then we extract a chroma feature from the decoded audio data to achieve audio identification. The experimental results show the evaluations of the format classification, fragment recovery and audio identification.