Day by day, biometric-based systems play a vital role in our daily lives. This paper proposed an intelligent assistant intended to identify emotions via voice message. A biometric system has been developed detect human based on recognition and control few electronic peripherals for alert actions. smart aims provide support the people through buzzer light emitting diodes (LED) signals it also ke...

Reward-based learning can easily be applied to real life with a prevalence in children teaching methods. It also allows machines and software agents to automatically determine the ideal behavior from a simple reward feedback (e.g., encouragement) to maximize their performance. Advancements in affective computing, especially emotional speech processing (ESP) have allowed for more natural interac...

Emotion recognition from speech has developed as a recent research area in Human–Computer Interaction. The objective of this paper is to use a 3-stage Support Vector Machine classifier to classify seven different emotions present in the Berlin Emotional Database. For the purpose of classification, MFCC features from all the 535 files present in the database are extracted. Nine statistical measu...

There are may exist some common factors independent of languages and cultures in human perception of emotion via speech sounds. This study investigated the factors using subjects from Japan, the United States and China, all of whom have no experience living abroad. An emotional speech database sans linguistic information was used in this study and evaluated using 3and 6-emotional dimensions. It...

Recently, the importance of reacting to the emotional state of a user has been generally accepted in the field of human-computer interaction and especially speech has received increased focus as a modality from which to automatically deduct information on emotion. So far, mainly academic and not very application-oriented offline studies based on previously recorded and annotated databases with ...

The voice embodies three sources of information: speech, the identity, and the emotional state of the speaker (i.e., emotional prosody). The latter feature is resembled by the variability of the F0 (also named fundamental frequency of pitch) (SD F0). To extract this feature, Emotional Prosody Measurement (EPM) was developed, which consists of 1) speech recording, 2) removal of speckle noise, 3)...

The voice embodies three sources of information: speech, the identity, and the emotional state of the speaker (i.e., emotional prosody). The latter feature is resembled by the variability of the F0 (also named fundamental frequency of pitch) (SD F0). To extract this feature, Emotional Prosody Measurement (EPM) was developed, which consists of 1) speech recording, 2) removal of speckle noise, 3)...

Emotional speech recognition is the problem of discriminating speech samples by their emotional content. Our solution to this problem lies on three areas: signal processing, computational linguistics, and statistical learning. At signal processing and computational linguistics levels, identification and extraction of speech features is concerned; proposed in this work is a set of acoustic and l...

The StarGANv2-VC model is a many-to-many non-parallel generative adversarial network (GAN) voice conversion (VC) that has proven effective in style tasks. This study aimed to investigate the scalability and diversity of for English emotional (EVC) across different speakers emotions. We carried out five experiments using an Emotional Speech Database (ESD), comprising single speaker-multi-emotion...

Javanese is one of the most widely spoken regional languages in Indonesia, alongside other languages. Emotions can be recognized a variety ways, including facial expression, behavior, and speech. The recognition emotions through speech straightforward process, but outcomes are quite significant. Currently, there no database for identifying This paper aims to describe creation emotional database...