• Title/Summary/Keyword: 감정 음성

Search Result 235, Processing Time 0.021 seconds

Improved speech emotion recognition using histogram equalization and data augmentation techniques (히스토그램 등화와 데이터 증강 기법을 이용한 개선된 음성 감정 인식)

  • Heo, Woon-Haeng;Kwon, Oh-Wook
    • Phonetics and Speech Sciences
    • /
    • v.9 no.2
    • /
    • pp.77-83
    • /
    • 2017
  • We propose a new method to reduce emotion recognition errors caused by variation in speaker characteristics and speech rate. Firstly, for reducing variation in speaker characteristics, we adjust features from a test speaker to fit the distribution of all training data by using the histogram equalization (HE) algorithm. Secondly, for dealing with variation in speech rate, we augment the training data with speech generated in various speech rates. In computer experiments using EMO-DB, KRN-DB and eNTERFACE-DB, the proposed method is shown to improve weighted accuracy relatively by 34.7%, 23.7% and 28.1%, respectively.

Speech Emotion Recognition by Speech Signals on a Simulated Intelligent Robot (모의 지능로봇에서 음성신호에 의한 감정인식)

  • Jang, Kwang-Dong;Kwon, Oh-Wook
    • Proceedings of the KSPS conference
    • /
    • 2005.11a
    • /
    • pp.163-166
    • /
    • 2005
  • We propose a speech emotion recognition method for natural human-robot interface. In the proposed method, emotion is classified into 6 classes: Angry, bored, happy, neutral, sad and surprised. Features for an input utterance are extracted from statistics of phonetic and prosodic information. Phonetic information includes log energy, shimmer, formant frequencies, and Teager energy; Prosodic information includes pitch, jitter, duration, and rate of speech. Finally a patten classifier based on Gaussian support vector machines decides the emotion class of the utterance. We record speech commands and dialogs uttered at 2m away from microphones in 5different directions. Experimental results show that the proposed method yields 59% classification accuracy while human classifiers give about 50%accuracy, which confirms that the proposed method achieves performance comparable to a human.

  • PDF

A Study of FO's realization in Emotional speech (감정에 따른 음성의 기본주파수 실현 연구)

  • Park, Mi-Young;Park, Mi-Kyoung
    • Proceedings of the KSPS conference
    • /
    • 2005.11a
    • /
    • pp.79-85
    • /
    • 2005
  • In this Paper, we are trying to compare the normal speech with emotional speech -happy, sad, and angry states- through the changes of fundamental frequency. Based on the distribution charts of the normal and emotional speech, there are distinctive cues such as range of distribution, average, maximum, minimum, and so on. On the whole, the range of the fundamental frequency is extended in happy and angry states. On the other hand, sad states make the range relatively lessened. Nevertheless, the ranges of the 10 frequency in sad states are wider than the normal speech. In addition, we can verify that ending boundary tones reflect the information of whole speech.

  • PDF

Design of a Mirror for Fragrance Recommendation based on Personal Emotion Analysis (개인의 감성 분석 기반 향 추천 미러 설계)

  • Hyeonji Kim;Yoosoo Oh
    • Journal of Korea Society of Industrial Information Systems
    • /
    • v.28 no.4
    • /
    • pp.11-19
    • /
    • 2023
  • The paper proposes a smart mirror system that recommends fragrances based on user emotion analysis. This paper combines natural language processing techniques such as embedding techniques (CounterVectorizer and TF-IDF) and machine learning classification models (DecisionTree, SVM, RandomForest, SGD Classifier) to build a model and compares the results. After the comparison, the paper constructs a personal emotion-based fragrance recommendation mirror model based on the SVM and word embedding pipeline-based emotion classifier model with the highest performance. The proposed system implements a personalized fragrance recommendation mirror based on emotion analysis, providing web services using the Flask web framework. This paper uses the Google Speech Cloud API to recognize users' voices and use speech-to-text (STT) to convert voice-transcribed text data. The proposed system provides users with information about weather, humidity, location, quotes, time, and schedule management.

Development of Driver's Emotion and Attention Recognition System using Multi-modal Sensor Fusion Algorithm (다중 센서 융합 알고리즘을 이용한 운전자의 감정 및 주의력 인식 기술 개발)

  • Han, Cheol-Hun;Sim, Kwee-Bo
    • Journal of the Korean Institute of Intelligent Systems
    • /
    • v.18 no.6
    • /
    • pp.754-761
    • /
    • 2008
  • As the automobile industry and technologies are developed, driver's tend to more concern about service matters than mechanical matters. For this reason, interests about recognition of human knowledge and emotion to make safe and convenient driving environment for driver are increasing more and more. recognition of human knowledge and emotion are emotion engineering technology which has been studied since the late 1980s to provide people with human-friendly services. Emotion engineering technology analyzes people's emotion through their faces, voices and gestures, so if we use this technology for automobile, we can supply drivels with various kinds of service for each driver's situation and help them drive safely. Furthermore, we can prevent accidents which are caused by careless driving or dozing off while driving by recognizing driver's gestures. the purpose of this paper is to develop a system which can recognize states of driver's emotion and attention for safe driving. First of all, we detect a signals of driver's emotion by using bio-motion signals, sleepiness and attention, and then we build several types of databases. by analyzing this databases, we find some special features about drivers' emotion, sleepiness and attention, and fuse the results through Multi-Modal method so that it is possible to develop the system.

Acoustic parameters for induced emotion categorizing and dimensional approach (자연스러운 정서 반응의 범주 및 차원 분류에 적합한 음성 파라미터)

  • Park, Ji-Eun;Park, Jeong-Sik;Sohn, Jin-Hun
    • Science of Emotion and Sensibility
    • /
    • v.16 no.1
    • /
    • pp.117-124
    • /
    • 2013
  • This study examined that how precisely MFCC, LPC, energy, and pitch related parameters of the speech data, which have been used mainly for voice recognition system could predict the vocal emotion categories as well as dimensions of vocal emotion. 110 college students participated in this experiment. For more realistic emotional response, we used well defined emotion-inducing stimuli. This study analyzed the relationship between the parameters of MFCC, LPC, energy, and pitch of the speech data and four emotional dimensions (valence, arousal, intensity, and potency). Because dimensional approach is more useful for realistic emotion classification. It results in the best vocal cue parameters for predicting each of dimensions by stepwise multiple regression analysis. Emotion categorizing accuracy analyzed by LDA is 62.7%, and four dimension regression models are statistically significant, p<.001. Consequently, this result showed the possibility that the parameters could also be applied to spontaneous vocal emotion recognition.

  • PDF

A Study on Motion Control of the Pet-Robot using Voice-Recognition (음성인식을 이용한 반려 로봇의 모션제어에 대한 연구)

  • Ye-Jin, Cho;Hyun-Seok, Kim;Tae-Sung, Bae;Su-Haeng, Lee;Jin-Hyean, Kim;Jae-Wook, Kim
    • The Journal of the Korea institute of electronic communication sciences
    • /
    • v.17 no.6
    • /
    • pp.1089-1094
    • /
    • 2022
  • In this paper, a human coexistence-type companion robot that can communicate with people in daily life and alleviate the gap in care personnel was studied. Based on the voice recognition module, servo motor, and Arduino board, a companion robot equipped with a robot arm control function using voice recognition, a position movement function using RC cars, and a voice recognition function was tested and manufactured. As a result of the experiment, the speech recognition experiment according to distance showed the optimal recognition rate at a distance of 5 to 30 cm, and the speech recognition experiment according to gender showed a higher recognition rate in the first tone, monotonous tone. Through the evaluation results of these motion experiments, it was confirmed that a companion robot could be made.

Design and Implementation of A Personalized Home Network Service System based on Emotion Analysis (감정 분석을 통한 개인화 홈 네트워크 서비스 시스템의 설계 및 구현)

  • Kim, Jun-Su;Kim, Dong-Yub;Bin, Sung-Hwan;Kim, Dae-Young;Ryu, Min-Woo;Cho, Kuk-Hyun
    • Journal of the Institute of Electronics Engineers of Korea CI
    • /
    • v.47 no.6
    • /
    • pp.131-138
    • /
    • 2010
  • As ubiquitous computing environments evolve, various services are being provided as customer-centric services. In the past, studies based on personal profiles have been conducted to provide personalized services. However, identifying the user's preferences and supporting personalized services requires considerable data and time. To solve these problems, this paper proposes a system which provides the service by analyzing the user's emotions, rather than personalized service with personal profiles. In the proposed system, both speech analysis method and image analysis method are used to analyze the user's emotion. By using this emotion analysis method, we implemented the proposed system within the home network environment and finally provide effective personalized service.

A Study on the Influence of Emotional Labor and Social Support on Airline Call Center Agent Burnout (항공사 콜센터 상담원의 감정노동과 사회적 지원이 소진에 미치는 영향 연구)

  • Kwon, Mi-Kyung;Yoon, Sun-Young
    • Journal of Advanced Navigation Technology
    • /
    • v.15 no.5
    • /
    • pp.808-822
    • /
    • 2011
  • In the subject experiment of this paper, contrary to the existing thesis about the emotional labor of people in the face-to-face service industry, I have chosen call center agents as they are primary first point of contact with customers in the airline industry. The main purpose of this experiment is to understand the relationship in between workplace burnout and emotional labor. In this study, I have investigated the following concepts; the effect of mediation on emotional labor, the different levels of emotional labor, and recommendations for improvement of competitive power to the call center agent as a member of the organization. The main results of experiment are as follows. First, the emotional labor given by the airline call center agents affects the rate of burnout. Second, support from workplace superiors showed that mediation had an effect on the relationship between emotional labor and burnout, however support from co-workers had no effect whatsoever. It is hope that this paper would supply information to give a competitive edge for airline call centers and their agents.

Automatic Speaker Identification in Fairytales towards Robot Storytelling (로봇 동화 구연을 위한 동화 상 발화문의 화자 자동파악)

  • Min, Hye-Jin;Kim, Sang-Chae;Park, Jong C.
    • Annual Conference on Human and Language Technology
    • /
    • 2012.10a
    • /
    • pp.77-83
    • /
    • 2012
  • 본 연구에서는 로봇의 자동 동화구연을 목표로 발화문장 상의 감정 파악 및 등장인물 별 다앙한 TTS 보이스 선택에 활용 가능한 발화문장의 화자 파악문제를 다룬다. 본 연구에서는 기존 규칙기반 방법론에서 많이 활용되어온 자질인 후보의 위치, 화자 후보의 주격/목적격 여부, 발화동사 존재 여부를 비롯하여 동화에 자주 나타나는 등장인물의 의미적 분류 및 등장인물의 등장/퇴장과 관련된 동사들을 추가 자질로 활용한다. 사람 및 동식물, 무생물이 모두 화자가 될 수 있는 동화 코퍼스에서 제안한 자질들을 활용하여 의사결정트리로 학습 및 검증한 결과 규칙기반의 베이스라인 방법에 비해 최대 49%의 정확도가 향상되었고, 제안한 방법론이 데이터의 변화에도 강인한 것을 확인할 수 있었다.

  • PDF