• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.144-156
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• 2021

This study was conducted to explore important factors to consider when designing voice-based psychological counseling agents amid the increasing use of conversational agents in counseling and psychotherapy. 48 participants selected their preferred agent's voice among four types (young women and men, middle-aged women and men) and had a conversation with a psychological counseling agent. They also evaluated the reasons for voice selection, mood changes, perception of the agent's characteristics, and counseling outcomes. As a results, the agent's voice type selected according to the user's gender was not statistically significant. However, the qualitative analysis showed 'comfort' of the voice was an important factor. Next, the user's mood improved significantly after the conversation with the agent, which confirmed the intervention effect. Finally, it was found that expertness and attractiveness perceptions toward the agent contributed to the counseling outcomes. The implications of the study and suggestions for future research were discussed.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04b
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• pp.1017-1020
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• 2002

학교교육에서 가장 필요한 요소인 상담을 온라인 상에서 가능하게 한 본 시스템은 웹상에서 사용 가능한 상담시스템으로 홈페이지를 통해 간단히 사용할 수 있으며, 1:1상담, 음성상담, 화상상담 등의 기본적인 상담 외에 인터넷 감시 기능을 통해 학생들의 불건전 사이트 접속을 막을 수 있는 특징이 있다. 또한 학생, 교사, 학부모간의 원활한 의사소통을 통해 학생에게는 보람있는 학교생활을, 교사와 학부모에게는 학생에 대한 올바른 이해를, 교사에게는 학생지도의 자신감과 사명감을 심어 줄 수 있는 특징이 있다.

• Journal of Internet Computing and Services
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• v.13 no.3
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• pp.107-114
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• 2012

In this paper, we proposed an automatic monitoring system for contact center in order to manage customer's complaint and agent's quality. The proposed system allows more accurate monitoring using emotion recognition and keyword spotting method for neutral/anger voice emotion. The system can provide professional consultation and management for the customer with language violence, such as abuse and sexual harassment. We developed a method of building robust algorithm on heterogeneous speech DB of many unspecified customers. Experimental results confirm the stable and improved performance using real contact center speech data.

• Smart Media Journal
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• v.11 no.8
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• pp.65-72
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• 2022

Due to COVID-19, the importance of non-face-to-face counseling is increasing as the face-to-face counseling method has progressed to non-face-to-face counseling. The advantage of non-face-to-face counseling is that it can be consulted online anytime, anywhere and is safe from COVID-19. However, it is difficult to understand the client's mind because it is difficult to communicate with non-verbal expressions. Therefore, it is important to recognize emotions by accurately analyzing text and voice in order to understand the client's mind well during non-face-to-face counseling. Therefore, in this paper, text data is vectorized using FastText after separating consonants, and voice data is vectorized by extracting features using Log Mel Spectrogram and MFCC respectively. We propose a multi-emotion recognition model that recognizes five emotions using vectorized data using an LSTM model. Multi-emotion recognition is calculated using RMSE. As a result of the experiment, the RMSE of the proposed model was 0.2174, which was the lowest error compared to the model using text and voice data, respectively.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.28 no.1
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• pp.11-13
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• 2017

This article addresses the roles of the speech language pathologist (SLP) for singers who require prompt and effective treatment when a voice problem arises. The causes of voice problem are often vocal abuse/misuse/overuse, muscle tension dysphonia and inappropriate singing technique. The SLP should conduct voice counseling and voice assessment for maintaining healthy voice of singer constantly.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.1243-1246
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• 2006

초고속 통신망의 확대 적용으로 인터넷의 빠른 성장과 함께 음성과 비디오 그리고 데이터를 통합하고자 하는 노력이 시도되고 있다. VoIP(Voice over IP)는 IP를 이용하여 음성과 데이터를 패킷 형태로 통합하여 실시간으로 전송하는 기술이다[1]. 패킷 네트워크에서 VoIP 시그널링 기술을 이용하면 망 자원으 효율적 이용 및 PSTN에 가까운 음질 그리고 인터넷과 연계한 다양한 음성서비스 지원이 가능하다. 콜센터에서도 VoIP를 사용하게 됨에 따라 VoIP망에서의 녹취 시스템이 필요하다. VoIP 녹취 시스템은 상담원과 고객 간의 통화 내용을 자동으로 녹음하여 보관함으로써 고객의 요구사항을 명확하게 파악할 수 있으며 녹취 데이터의 통계 자료 제공으로 효율적인 관리가 가능하고, 선택 녹취, 스케쥴링 녹취, 상담원의 평가 자료를 제공하여 고객 관리의 질적인 향상을 지원한다. 본 논문에서는 성능에 큰 영향을 주지 않고 기존의 VoIP 녹취 시스템의 문제점을 해결한 에이전트를 포함한 VoIP 녹취 시스템을 제안한다.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.69-75
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• 2021

In a contact-free society, online services are becoming more important than classic offline services. At the same time, the role of a contact center, which executes customer relation management (CRM), is increasingly essential. For supporting the CRM tasks and their effectiveness, techniques of process automation need to be applied. Quality assurance (QA) is one of the time and resource consuming, and typical processes that are suitable for automation. In this paper, a method of automatic quality evaluation for voice based consultations is proposed. Firstly, the speech in consultations is transformed into a text by speech recognition. Then quantitative evaluation based on the QA metrics, including checking the elements in opening and closing mention, the existence of asking the mandatory information, the attitude of listening and speaking, is executed. 92.7% of the automated evaluations are the same to the result done by human experts. It was found that the non matching cases of the automated evaluations were mainly caused from the mistranslated Speech-to-Text (STT) result. With the confidence of STT result, this proposed method can be employed for enhancing the efficiency of QA process in contact centers.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.327-333
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• 2021

Currently development of the Artificial Intelligence technology is rapidly progressing in the era of the Fourth Industrial Revolution. The government is trying to improve the education of Artificial Intelligence and cultivating human resources. However there are very few cases where A.I technology is actually used in public education classes. Therefore we designed a text repository by implementing A.I speech recognition to provide career counseling for elementary school students. In the meantime, there have been many difficulties in giving advance consultations required for students' career counseling. In this study we suggested A.I speech recognition technology which can solve addressed problem and we planned various ways to make the program more educational. To conclude we expect A.I technology implemented in this study provides effective solution to career counseling.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06c
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• pp.287-290
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• 1994

음성 인식 시스템의 개발을 위해서는 음성 데이터베이스구축이 중요한 과제의 하나로서, 많은 시간과 노력이 요구된다. 개별적인 음성데이타베이스 구축에 따른 중복 투자를 줄이고 다양한 인식 알고리듬의 성능 비교와 국내 음성 인식 기술의 발전을 위해서는 벤치마크 시험을 위한 공통의 음성 데이터베이스가 필수적이다. 본 논문에서는 한국과학기술원 통신연구실에서 제작한 한국어 음성 데이터베이스에 관하여 기술한다. KAIST 음성데이타베이스는 자동통ㅇ역을 N이한 무역 상담과 관련되 3,000 단어 규모의 연속어를 비롯하여, 가변 길이 연결 숫자음, phoneme-balanced 75 고립단어, 지역명 관련 500 고립단어, 한국어 아-세트로 구성되어 있다. 이 음성 데이터베이스의 구축을 위하여 사용된 태스크선정 절차, 녹음 방법, 규격, 및 기대효과 등 세부사항을 기술한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.750-762
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• 2019

The importance of the call center as a contact point for the enterprise is growing. However, call centers have difficulty with their operating agents due to the agents' lack of knowledge and owing to frequent agent turnover due to downturns in the business, which causes deterioration in the quality of customer service. Therefore, through an N-bank call center case study, we developed a system to reduce the burden of keeping up business knowledge and to improve customer service quality. It is a "real-time agent advisor" system that provides agents with answers to customer questions in real time by combining AI technology for speech recognition, natural language processing, and questions & answers for existing call center information systems, such as a private branch exchange (PBX) and computer telephony integration (CTI). As a result of the case study, we confirmed that the speech recognition system for real-time call analysis and the corpus construction method improves the natural speech processing performance of the query response system. Especially with name entity recognition (NER), the accuracy of the corpus learning improved by 31%. Also, after applying the agent advisor system, the positive feedback rate of agents about the answers from the agent advisor was 93.1%, which proved the system is helpful to the agents.