Speech signal in addition to the linguistic information contains additional information about the speaker: age, gender, social status, accent (foreign accent, dialects, etc.), emotional state, health etc. Some of these informational channels induce changes of the speech acoustic characteristics. This article presents evaluation of the ASR acoustic models (first trained on neutral, read speech) ...

The research work describes the procedure and the development of Isolated Marathi Emotional Speech Database. The database consists of samples, collected from 50 speakers including males and females who simulated the emotions producing by the Marathi utterances which are used in everyday communication and are interpretable in all applied emotions. The speech samples were enhanced by spectral sub...

The paper introduced the present status of speech emotion recognition. In order to improve the single-mode emotion recognition rate, the bimodal fusion method based on speech and facial expression was proposed. The emotional databases of Chinese speech and facial expressions were established with the noise stimulus and movies evoking subjects' emtion. On the foundation, we analyzed the acoustic...

Emotional speech recognition has been studied using different approaches, which some works use real emotions and other uses acted ones, usually real emotional speech databases include like two or three emotions and acted ones have five or more, for this work Berlin Emotional Speech Database [1] was selected due to its availability, which has 535 sentences expressed in seven emotions (anger, bor...

Emotion recognition from human speech is a challenge for the researchers. It is mostly considered under ideal acoustic conditions. The performance of such system is degraded while there is existence of environmental mismatches between training and testing phases. For robust speech recognition it requires for reduction of redundancy, variability, and capturing ability of speech signals in noisy ...

Emotional information recognition is an important application in the field of artificial intelligence. This paper analyzes existing speech emotion system, based on improved neural network strategy to improve accuracy recognition, through combination convolution (CNN) and long-term short-term (LSTM), emotional data successfully recognized, better obtained.

An approach for the recognition of emotions in speech is presented. The target language is Mexican Spanish, and for this purpose a speech database was created. The approach consists in the phoneme acoustic modelling of emotion-specific vowels. For this, a standard phoneme-based Automatic Speech Recognition (ASR) system was built with Hidden Markov Models (HMMs), where different phoneme HMMs wer...

The basal ganglia (BG) have repeatedly been linked to emotional speech processing in studies involving patients with neurodegenerative and structural changes of the BG. However, the majority of previous studies did not consider that (i) emotional speech processing entails multiple processing steps, and the possibility that (ii) the BG may engage in one rather than the other of these processing ...