## 3 Korean Emotional Speech Database  
The study of emotion recognition has rapidly developed over the last decade with broad interest from researchers in neuroscience, computer science, psychiatry, psychology, audiology, and computer science. The key of these studies is to secure the availability of validated and reliable expressions of emotion. Most emotion data sets include either facial expressions or speech recordings. Among data sets, few contain audio-visual recordings of speakers in Korean. This study constructs a K-EmoDB and reports validity and reliability of the data based on ratings from participants. The database was recorded with Korean utterances from professional actors. All recorded data was recorded in a professional studio, considering the sound quality of the data by eliminating any background noise. The database was recorded using two different methods: (1) A method of recording the emotions using 120 emotion-inducing scenarios (20 of each emotion) according to each emotion. (2) A method of recording 20 emotionless sentences that did not affect the emotions in the 6-emotion version.  
The database was recorded with Korean utterances from 20 professional actors (M = 28.1, SD = 3.41, age range = 23-35, 11 males and 9 females). To be eligible, actors needed to have Korean as their first language, to speak with a neutral Seoul accent, and to not possess any distinctive features. Participants were also required to identify text presented at a distance of 1.5 m. Figure 1a shows an actual actor during recording.  
We chose six emotions for the experiment: neutral, anger, happiness, sadness, fear, and excitement. Here, \"Excitement\" refers to a more delighted with excitement emotion than \"happiness\". Neutrality was selected as the baseline emotion, and the remaining states consisted of the set of five basic or fundamental emotions that are thought to be culturally universal. The concept of primary emotions has a long history in science and philosophy. While the discrete model of emotion has been criticized [41; 42; 43], it is a practical choice for the creation and labelling of emotion sets [21]. Therefore, the six emotions can be found in most existing sets [44; 45; 46; 47; 48; 49; 50; 51; 52; 53; 54].  
K-EmoDB was created using the following procedure. Actors were recruited through online casting, and 20 actors were selected by audition. All data were recorded in a  
Figure 1: (**a**) One of the actors during recording (**b**) Recording equipment.  
professional studio, in order to optimize the sound quality of the data by eliminating any background noise. The Neumann TLM 103, Neumann U87 Ai, Oktava MK-319 microphone, and Universal Audio LA-610 MK1, WARM AUDIO WA76, MPAC-01 mixers were used for recording, as shown in Figure 1b. Each person recorded 120 sentences. Each speech data point is approximately three to five seconds long. All speech emotion data were recorded at 48 kHz, and downsampling was performed with a 16 kHz downsampling rate in a PCM signed 16-bit format.  
To ensure the emotional quality and naturalness of the data, an evaluation test was carried out with seven subjects. The subjects listened to each sample and had to decide on an emotion score from 5 to 1. If subjects felt that the emotion was clearly contained in the speech data, they gave it a score of 5. However, if subjects felt that the speech data did not include the emotion, they give it a score of 1. Using to the evaluation results, 150 emotion data points in each category were chosen to construct the final K-Emo DB database. The final data consists of male and female speech files in a ratio of 50 to 50.