Update README.md

README.md

@@ -30,6 +30,7 @@ This dataset consists of 5 main emotions assigned to actors: Neutral, Anger, Hap
 
 The THAI SER contains 100 recordings and is separated into two main categories: Studio and Zoom. Studio recordings also consist of two studio environments: Studio A, a controlled studio room with soundproof walls, and Studio B, a normal room without soundproof or noise control. Thus the recording environment can be concluded as follows:
 
+```
 StudioA (noise controlled, soundproof wall)
 └─ studio001
 └─ studio002
@@ -47,6 +48,8 @@ Zoom (Recorded online via Zoom and Zencastr)
 └─ zoom002
 ...
 └─ zoom020
+```
+
 Each recording is separated into two sessions: Script Session and Improvisation Session.
 
 To mapped each utterance to an emotion, we use majority voted of answer from 3-8 annotators which collected from crowdsourcing (wang.in.th).
@@ -56,19 +59,21 @@ To mapped each utterance to an emotion, we use majority voted of answer from 3-8
 Script session
 
 In the script session, the actor was assigned three sentences:
+```
 sentence 1: พรุ่งนี้มันวันหยุดราชการนะรู้รึยัง หยุดยาวด้วย
             (Do you know tomorrow is a public holiday and it's the long one.)
 sentence 2: อ่านหนังสือพิมพ์วันนี้รึยัง รู้ไหมเรื่องนั้นกลายเป็นข่าวใหญ่ไปแล้ว
             (Have you read today's newspaper, that story was the topliner.)
 sentence 3: ก่อนหน้านี้ก็ยังเห็นทำตัวปกติดี ใครจะไปรู้หล่ะ ว่าเค้าคิดแบบนั้น
             (He/She was acting normal recently, who would thought that he/she would think like that.)
+```
 The actor was asked to speak each sentence two times for each emotion with two emotional intensity levels (normal, strong), with an additional neutral expression.
 
 
 
 Improvisation session
 For the Improvisation session, two actors were asked to improvised according to provided emotion and scenario.
-
+```
 Scenarios	Actor A	Actor B
 1	(Neutral) A hotel receptionist trying to explain and service the customer	(Angry) A angry customer who dissatisfy the hotel services
 2	(Happy) A person excitingly talking with B about his/her marriage plan	(Happy) A person happily talking with A and help him/her plan his ceremony
@@ -85,13 +90,13 @@ Scenarios	Actor A	Actor B
 13	(Neutral) A patient inquire information	(Happy) A happy doctor telling his/her patience more information
 14	(Angry) A person who upset with his/her work	(Neutral) A calm friend who listened to another person's problem
 15	(Sad) A person sadly tell another person about a relationship	(Angry) A person who feels angry after listening to another person's bad relationship
-
+```
 
 File naming convention
 Each of files has a unique filename, provided in .flac format with sample rate about 44.1 KHz. The filename consists of a 5 to 6-part identifier (e.g., s002_clip_actor003_impro1_1.flac, s002_clip_actor003_script1_1_1a.flac). These identifiers define the stimulus characteristics:
 
 File Directory Management
-
+```
 studio (e.g., studio1-10)
 └─ <studio-num> (studio1, studio2, ...)
     └─ <mic-type> (con, clip, middle)
@@ -101,8 +106,9 @@ zoom (e.g., zoom1-10)
 └─ <zoom-num> (zoomo1, zoom2, ...)
     └─ <mic-type> (mic)
         └─ <audio-file> (.flac)
+```
 Filename identifiers
-
+```
 Recording ID (s = studio recording, z = zoom recording)
 
 Number of recording (e.g., s001, z001)
@@ -140,9 +146,10 @@ Improvisation session, scenario 1 (impro1)
 Other Files
 emotion_label.json - a dictionary for recording id, assigned emotion (assigned_emo), majority emotion (emotion_emo), annotated emotions from crowdsourcing (annotated), and majority agreement score (agreement)
 actor_demography.json - a dictionary that contains information about the age and sex of actors.
-
+```
 
 Version
+```
 Version 1 (26 March 2021): Thai speech emotion recognition dataset THAI SER contains 100 recordings (80 studios and 20 zooms) which is 41 hours 36 minutes long which contain 27,854 utterances and be labeled 27,854 utterances.
 Dataset statistics
 Recording environment	Session	Number of utterances	Duration(hrs)
@@ -151,7 +158,7 @@ Improvisation	3,606	5.8860
 Studio (80)	Script	9,582	13.6903
 Improvisation	12,268	18.0072
 Total (100)		27,854	41.6114
-
+```
 
 Dataset sponsorship and license