Along with automatic speech recognition, many researchers have been actively studying emotion since information is as crucial the textual for effective interactions. Emotion can be divided into categorical and dimensional emotion. Although widely used, emotion, typically represented arousal valence, provide more detailed on emotional states. Therefore, in this paper, we propose a Conformer-base...

Cultural differences have been one of the many factors that can cause failures in speech emotion analysis. If this cultural parameter could be regarded as noise artifacts in detecting emotion in speech, we could then extract pure emotion speech signal from the raw emotional speech. In this paper we use the amplitude spectral subtraction (ASS) method to profile the emotion from raw emotional spe...

The present work studies the effect of emotional speech on a smarthome application. Specifically, we evaluate the recognition performance of the automatic speech recognition component of a smart-home dialogue system for various categories of emotional speech. The experimental results reveal that word recognition rate for emotional speech varies significantly across different emotion categories.

In speech recognition and emotion recognition from speech, qualitatively high transcription and annotation of given material is important. To analyse prosodic features, linguistics provides several transcription systems. Furthermore, in emotion labelling different methods are proposed and discussed. In this paper, we introduce the tool ikannotate, which combines prosodic information with emotio...

The purpose of speech emotion recognition system is to classify speaker's utterances into different emotional states such as disgust, boredom, sadness, neutral and happiness. Speech features that are commonly used in speech emotion recognition (SER) rely on global utterance level prosodic features. In our work, we evaluate the impact of frame-level feature extraction. The speech samples are fro...

The interest in emotion recognition from speech has increased in the last decade. Emotion recognition can improve the quality of services and the quality of life of people. One of the main problems in emotion recognition from speech is to find suitable features to represent the phenomenon. This paper proposes new features based on the energy content of wavelet based time-frequency (TF) represen...

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 impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development...

With exponentially evolving technology it is no exaggeration to say that any interface for human-robot interaction (HRI) that disregards human affective states and fails to pertinently react to the states can never inspire a user’s confidence, but they perceive it as cold, untrustworthy, and socially inept. Indeed, there is evidence that HRI is more likely to be accepted by the user if it is se...