Speech Emotion Recognition Framework based on User Self-referential Speech Features

Noh, Kyoung-Ju; Chung, Seungeun; Lim, Jiyoun; Kim, Gague; Jeong, Hyuntae

doi:10.1109/gcce.2018.8574676

Cited by 4 publications

(1 citation statement)

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“…In the dictionary-based approach is to identify the emotional words in a dictionary and it is also finding their antonyms and synonyms to enlarge the basic list of emotion.on another hand corpus-based approach begins with a seed list of emotional words an enlarge the database by searching different word with context-specific features in a huge corpus. [2] in 2018 proposes a method of speech emotion recognition (SER) system utilizing client self-referential speech characteristics. Which follow the ROC (Rate of change) of the relating characteristics an incentive as according to the client's emotional states.…”

Section: Knowledge-based Techniques:-mentioning

confidence: 99%

Design & Development of Network Geo-Fencing Model for User Monitoring and it’s Alertness in a Security Applications

Barapatre¹,

Deshmukh²

2019

IJRAT

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Communication plays a vital role according to the people's emotion, as emotions and gesture play 80% role while communication. Nowadays emotion recognition and classification are used in different areas to understand the human feelings like in the robotics, Health care, Military, Home automation, Hands-free computing, Mobile Telephony, Video game,call-center system, Marketing, etc. SER can help better interaction between the machine and the human. There are various algorithms and combination of the algorithms are available to recognize and classify the audio according to their emotion. In this paper, we attempted to investigate the episodic significant works, their technique and the impact of the approaches and the scope of the correction of the results.

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Section: Knowledge-based Techniques:-mentioning

confidence: 99%