http://www.ffri.hr/~ibrdar/komunikacija/seminari/Ververidis,%202006%20-%20Emotional%20speech%20recognition.pdf

Emotional speech recognition: Resources, features, and methods

Emotion recognition from speech has emerged as an important research area in the recent past. In this regard, review of existing work on emotional speech processing is useful for carrying out further research. In this paper, the recent literature on speech emotion recognition has been presented considering the issues related to emotional speech corpora, different types of speech features and models used for recognition of emotions from speech. Thirty two representative speech databases are reviewed in this work from point of view of their language, number of speakers, number of emotions, and purpose of collection. The issues related to emotional speech databases used in emotional speech recognition are also briefly discussed. Literature on different features used in the task of emotion recognition from speech is presented. The importance of choosing different classification models has been discussed along with the review. The important issues to be considered for further emotion recognition research in general and in specific to the Indian context have been highlighted where ever necessary.

/pdf/emotion-recognition-from-speech-a-review-2bhwxdu8ml.pdf

Emotion recognition from speech: a review

Text-to-Speech Synthesis provides a complete, end-to-end account of the process of generating speech by computer. Giving an in-depth explanation of all aspects of current speech synthesis technology, it assumes no specialized prior knowledge. Introductory chapters on linguistics, phonetics, signal processing and speech signals lay the foundation, with subsequent material explaining how this knowledge is put to use in building practical systems that generate speech. Including coverage of the very latest techniques such as unit selection, hidden Markov model synthesis, and statistical text analysis, explanations of the more traditional techniques such as format synthesis and synthesis by rule are also provided. Weaving together the various strands of this multidisciplinary field, the book is designed for graduate students in electrical engineering, computer science, and linguistics. It is also an ideal reference for practitioners in the fields of human communication interaction and telephony.

/pdf/text-to-speech-synthesis-2y7hiwoykk.pdf

Text-to-Speech Synthesis

2017 25th European Signal Processing Conference (EUSIPCO)

Attempts to add emotion effects to synthesised speech have existed for more than a decade now. Several prototypes and fully operational systems have been built based on different synthesis techniques, and quite a number of smaller studies have been conducted. This paper aims to give an overview of what has been done in this field, pointing out the inherent properties of the various synthesis techniques used, summarising the prosody rules employed, and taking a look at the evaluation paradigms. Finally, an attempt is made to discuss interesting directions for future development.

Emotional speech synthesis: a review.

Modern Speech synthesisers have achieved a high degree of intelligibility, but can not be regarded as natural-sounding devices. In order to decrease the monotony of synthetic speech, the implementation of emotional effects is now being progressively considered. This paper presents a through study of emotional speech in Spanish, and its application to TTS, presenting a prototype system that simulates emotional speech using a commercial synthesiser. The design and recording of a Spanish database will be described and also the analysis of the emotional prosody (by fitting the data to a formal model). Using this collected data, a rule-based simulation of three primary emotions was implemented in the Text-to-Speech system. Finally, the assessment of the synthetic voice through perception experiments will classify the system as capable of producing quality voice with recognisable emotional effects.

Emotional speech synthesis: from speech database to TTS.

The importance of speech prosody for conveying emotional information has been extensively underlined in the literature. Major elements such as pitch, tempo and stress are presented as the main acoustic correlates of emotion in human speech. Nevertheless, as several authors have shown, voice quality is also a relevant feature in emotion recognition. In this paper, we present the prosodic analysis, modelling and evaluation of the Spanish Emotional Speech Database including four emotions: happiness, sadness, cold anger and surprise. Our results show that, for Spanish, the contribution of prosody to the recognisability of the uttered emotion greatly varies from one to another, with sadness and surprise being more supra segmental, and happiness and cold anger being rather segmental.

/pdf/analysis-and-modelling-of-emotional-speech-in-spanish-1tdfwe0g2p.pdf

Analysis and modelling of emotional speech in spanish

Characterization of Dysphonic Voices by Means of a Filterbank-Based Spectral Analysis: Sustained Vowels and Running Speech

Currently, an essential point in speech synthesis is the addressing of the variability of human speech. One of the main sources of this diversity is the emotional state of the speaker. Most of the recent work in this area has been focused on the prosodic aspects of speech and on rule-based formantsynthesis experiments. Even when adopting an improved voice source, we cannot achieve a smiling happy voice or the menacing quality of cold anger. For this reason, we have performed two experiments aimed at developing a concatenative emotional synthesiser, a synthesiser that can copy the quality of an emotional voice without an explicit mathematical model.

Development of an emotional speech synthesiser in Spanish.

Accurate prediction of segmental duration from text in a textto-speech system is difficult for several reasons. One specially relevant is the great quantity of contextual factors that affect timing and how to model them. There are many parameters that affect duration, but not all of them are always relevant. We present a complete environment in which to decide which parameters are more relevant in different situations and the best way to code them. The system is based in a neural network absolutely configurable, and the main effort is made in the parameters to be used, including the contextual effects using windows of variable length.

Juana M. Gutiérrez-Arriola

Papers

Emotional speech synthesis: from speech database to TTS.

Analysis and modelling of emotional speech in spanish

Characterization of Dysphonic Voices by Means of a Filterbank-Based Spectral Analysis: Sustained Vowels and Running Speech

Development of an emotional speech synthesiser in Spanish.

Automatic modeling of duration in a Spanish text-to-speech system using neural networks.