• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.9
• /
• pp.5763-5768
• /
• 2014

Maintaining a voice color is important when compounding both the normal voice because an emotion is not expressed with various emotional voices in a single synthesizer. When a synthesizer is developed using the recording data of too many expressed emotions, a voice color cannot be maintained and each synthetic speech is can be heard like the voice of different speakers. In this paper, the speech data was recorded and the change in the voice color was analyzed to develop an emotional HMM-based speech synthesizer. To realize a speech synthesizer, a voice was recorded, and a database was built. On the other hand, a recording process is very important, particularly when realizing an emotional speech synthesizer. Monitoring is needed because it is quite difficult to define emotion and maintain a particular level. In the realized synthesizer, a normal voice and three emotional voice (Happiness, Sadness, Anger) were used, and each emotional voice consists of two levels, High/Low. To analyze the voice color of the normal voice and emotional voice, the average spectrum, which was the measured accumulated spectrum of vowels, was used and the F1(first formant) calculated by the average spectrum was compared. The voice similarity of Low-level emotional data was higher than High-level emotional data, and the proposed method can be monitored by the change in voice similarity.

• Journal of the Korea Convergence Society
• /
• v.11 no.9
• /
• pp.91-97
• /
• 2020

Use of voice-based interfaces that can interact with users is increasing as AI technology develops. To date, however, most of the research on voice-based interfaces has been technical in nature, focused on areas such as improving the accuracy of speech recognition. Thus, the voice of most voice-based interfaces is uniform and does not provide users with differentiated sensibilities. The purpose of this study is to add a emotional factor suitable for the AI interface. To this end, we have derived emotional factors that should be considered in designing voice interface. In addition, we looked at voice trends that differed from country to country. For this study, we conducted interviews with voice industry experts from Finland and Norway, countries that use their own independent languages.

• MALSORI
• /
• v.55
• /
• pp.119-130
• /
• 2005

The aim of this paper is to investigate some acoustical characteristics of the voice quality features from the emotional speech database. Six different parameters are measured and compared for 6 different emotions (normal, happiness, sadness, fear, anger, boredom) and from 6 different speakers. Inter-speaker variability and intra-speaker variability are measured. Some intra-speaker consistency of the parameter change across the emotions are observed, but inter-speaker consistency are not observed.

• Phonetics and Speech Sciences
• /
• v.7 no.4
• /
• pp.67-76
• /
• 2015

The purpose of this study was to compare professional (Pro) and non-professional (Non-pro) voice users with voice disorders in self-reporting voice evaluation using Korean-Voice Handicap Index (K-VHI) and Korean-Voice Related Quality of Life (K-VRQOL). In addition, those were compared by voice quality and voice disorder type. 94 Pro and 106 Non-pro were asked to fill out the K-VHI and K-VRQOL, perceptually evaluated on GRBAS scales, and divided into three types of voice disorders (functional, organic and neurologic) by an experienced speech-language pathologist and an otolaryngologist. The results showed that the functional (F) and physical (P) scores of K-VHI in Pro group were significantly higher than those in Non-pro group. As the voice quality evaluated by G scale got worse, the scores of all aspects except emotional (E) of K-VHI and social-emotional (SE) of K-VRQOL were higher. All scores of K-VHI and K-VRQOL in neurologic voice disorders were significantly higher than those in functional and organic voice disorders. In conclusion, professional voice users are more sensitive to their functional and physical handicap resulted by their voice problems and that goes double for the patients with severe and neurologic voice disorders.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.11
• /
• pp.159-166
• /
• 2014

In this paper, we examine the role of emotional acoustic cues including both prosody and voice quality parameters for the modification of a word sense. For the extraction of prosody parameters and voice quality parameters, we used 60 pieces of speech data spoken by six speakers with five different emotional states. We analyzed eight different emotional acoustic cues, and used a discriminant analysis technique in order to find the dominant sequence of acoustic cues. As a result, we found that anger has a close relation with intensity level and 2nd formant bandwidth range; joy has a relative relation with the position of 2nd and 3rd formant values and intensity level; sadness has a strong relation only with prosody cues such as intensity level and pitch level; and fear has a relation with pitch level and 2nd formant value with its bandwidth range. These findings can be used as the guideline for find-tuning an emotional spoken language generation system, because these distinct sequences of acoustic cues reveal the subtle characteristics of each emotional state.

• The Journal of the Acoustical Society of Korea
• /
• v.40 no.5
• /
• pp.523-529
• /
• 2021

In this paper, we designed and developed an Emotional Speech Synthesis Markup Language (SSML) processor. Multi-speaker emotional speech synthesis technology that can express multiple voice colors and emotional expressions have been developed, and we designed Emotional SSML by extending SSML for multiple voice colors and emotional expressions. The Emotional SSML processor has a graphic user interface and consists of following four components. First, a multi-speaker emotional text editor that can easily mark specific voice colors and emotions on desired positions. Second, an Emotional SSML document generator that creates an Emotional SSML document automatically from the result of the multi-speaker emotional text editor. Third, an Emotional SSML parser that parses the Emotional SSML document. Last, a sequencer to control a multi-speaker and emotional Text-to-Speech (TTS) engine based on the result of the Emotional SSML parser. Based on SSML which is a programming language and platform independent open standard, the Emotional SSML processor can easily integrate with various speech synthesis engines and facilitates the development of multi-speaker emotional text-to-speech applications.

• Journal of Internet Computing and Services
• /
• v.24 no.2
• /
• pp.11-18
• /
• 2023

Recently, in the field of Speech Emotion Recognition (SER), many studies have been conducted to improve accuracy using voice features and modeling. In addition to modeling studies to improve the accuracy of existing voice emotion recognition, various studies using voice features are being conducted. This paper, voice files are separated by time interval in a time series method, focusing on the fact that voice emotions are related to time flow. After voice file separation, we propose a model for classifying emotions of speech data by extracting speech features Mel, Chroma, zero-crossing rate (ZCR), root mean square (RMS), and mel-frequency cepstrum coefficients (MFCC) and applying them to a recurrent neural network model used for sequential data processing. As proposed method, voice features were extracted from all files using 'librosa' library and applied to neural network models. The experimental method compared and analyzed the performance of models of recurrent neural network (RNN), long short-term memory (LSTM) and gated recurrent unit (GRU) using the Interactive emotional dyadic motion capture Interactive Emotional Dyadic Motion Capture (IEMOCAP) english dataset.

• The Journal of the Acoustical Society of Korea
• /
• v.21 no.2E
• /
• pp.98-104
• /
• 2002

The present study describes a combination method to recognize the human affective states such as anger, happiness, sadness, or surprise. For this, we extracted emotional features from voice signals and facial expressions, and then trained them to recognize emotional states using hidden Markov model (HMM) and neural network (NN). For voices, we used prosodic parameters such as pitch signals, energy, and their derivatives, which were then trained by HMM for recognition. For facial expressions, on the other hands, we used feature parameters extracted from thermal and visible images, and these feature parameters were then trained by NN for recognition. The recognition rates for the combined parameters obtained from voice and facial expressions showed better performance than any of two isolated sets of parameters. The simulation results were also compared with human questionnaire results.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
• /
• v.26 no.1
• /
• pp.34-39
• /
• 2015

Background and Objectives:The Voice Handicap Index (VHI) evaluates the patients perception of impact of voice disorder in term of functional, physical, emotional factors. The purpose of this study was to evaluate the change of patient's subjective voice handicap index before and after laryngeal microsurgery for benign vocal cord lesions. Materials and Methods:We analyzed 55 patients who received laryngeal microsurgery for benign vocal cord disease from January 2011 to February 2013 retrospectively. There were 50 vocal nodules, 3 vocal polyps, 2 vocal cysts. VHI were analyzed before surgery and 3 months after surgery. Results:The VHI scores showed statistically significant reductions postoperatively in functional and emotional VHI (p=0.01 and p=0.034). Also, Emotional VHI score after microsurgery was higher in female than male [adjusted odd ratio (AOR)=0.292 ; 95% confidence interval, CI=0.098-0.869, p=0.01]. Conclusion:In other words, males experience significant more emotional effects that are improved after microscopic surgery.

• Korean Journal of Culture and Social Issue
• /
• v.25 no.1
• /
• pp.27-53
• /
• 2019

The purpose of this study is to investigate the influence of techno-overload and techno-invasion on emotional exhaustion and the mediating role of psychological contract breach. In addition, this study examines the moderating role of voice behavior in the relationship between techno-overload, techno-invasion and psychological contract breach. The results from 296 participants provided evidence that (1) techno-overload and techno-invasion are positively related to psychological contract breach, (2) psychological contract breach is positively related to emotional exhaustion, (3) psychological contract breach partially mediates the relationship between techno-overload, techno-invasion and emotional exhaustion, (4) voice behavior moderates the relationship between techno-overload, techno-invasion and psychological contract breach. Based on the results, implications of these findings, limitations, and future research are discussed in general discussion.