Expressive speech synthesis: a review

Govind, D.; Prasanna, S. R. Mahadeva

doi:10.1007/s10772-012-9180-2

Cited by 50 publications

(15 citation statements)

References 59 publications

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“…The collection of induced or spontaneous data is more challenging than acted data, thus such corpora turn to be not freely available. In the context of speech synthesis, acted data is recommended for cartoon animations or commercial applications while spontaneous data is better to deploy dialogue systems where the machine has to interact naturally with the user [12].…”

Section: Emotional Databasesmentioning

confidence: 99%

Can We Generate Emotional Pronunciations for Expressive Speech Synthesis?

Tahon

Lecorvé

Lolive

2020

IEEE Trans. Affective Comput.

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Abstract-In the field of expressive speech synthesis, a lot of work has been conducted on suprasegmental prosodic features while few has been done on pronunciation variants. However, prosody is highly related to the sequence of phonemes to be expressed. This article raises two issues in the generation of emotional pronunciations for TTS systems. The first issue consists in designing an automatic pronunciation generation method from text, while the second issue addresses the very existence of emotional pronunciations through experiments conducted on emotional speech. To do so, an innovative pronunciation adaptation method which automatically adapts canonical phonemes first to those labeled in the corpus used to create a synthetic voice, then to those labeled in an expressive corpus, is presented. This method consists in training conditional random fields pronunciation models with prosodic, linguistic, phonological and articulatory features. The analysis of emotional pronunciations reveals strong dependencies between prosody and phoneme assimilation or elisions. According to perceptual tests, the double adaptation allows to synthesize expressive speech samples of good quality, but emotion-specific pronunciations are too subtle to be perceived by testers.

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Section: Emotional Databasesmentioning

confidence: 99%

Can We Generate Emotional Pronunciations for Expressive Speech Synthesis?

Tahon

Lecorvé

Lolive

2020

IEEE Trans. Affective Comput.

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“…Text To Speech (TTS) is a system that is able to convert a text message into a relevant verbal message [8]. It is widely used to help build an easier communication, especially for whoever has a lack of visibility.…”

Section: Indonesian Text To Audio Visual Speechmentioning

confidence: 99%

Developing an Online Self-learning System of Indonesian Pronunciation for Foreign Learners

Muljono

Sumpeno

Arifianto

et al. 2016

Int. J. Emerg. Technol. Learn.

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Abstract-The main part of learning a language is pronunciation. In language learning method, pronunciation practice requires more portion than the language theory. There are some obstacles experienced by foreign learners to learn Indonesian because they are still strongly influenced by their mother tongue which is really different from Indonesian. There are some courses of learning Indonesian, indeed, but the foreign learners have to stay in Indonesia to join them. On the other hand, the researchers have successfully proven that the use of Information and Communication Technology (ICT) can help the learners in learning a language. In this paper, we have developed a system of the Online Self-Learning of Indonesian Pronunciation for Foreign Learner using Indonesian Text to Audio Visual Speech which is able to help the foreign learners to overcome their obstacles in learning Indonesian, especially the pronunciation. This system consists of 2(two) application modules: Indonesian Text to Speech (ITTS) and Indonesian Text to Audio Visual Speech (ITTAVS). In order to find out whether this system is feasible or not for foreign learners' skill in pronouncing the Indonesian words, a subjective measurement using subjective test Mean Opinion Score (MOS) is used. We organized native speakers (Indonesians) as the participants of this test. Some of them are lecturers of Indonesian language and can be considered as experts. The average scores (using MOS scale) of the tests given showed a promising result. This system is dedicated to the foreign learners who need to improve their skill in pronouncing the Indonesian words accurately and to change the classical method of learning into a self-learning method.

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“…The formulation multiplies all pitch values within a relevant time domain [t 1 , t 2 ] for a given modification factor which is governed by the variable α . The calculation is shown in equation (1).…”

Section: Pitchmentioning

confidence: 99%

“…Expressive speech is a form of speech synthesis aimed to improve the naturalness of neutral speech output of standard TTS [1]. Storytelling speaking style is a type of expressive speech that is important towards the development of digital storytelling [2] and a humanoid robot [3].…”

Section: Introductionmentioning

confidence: 99%

Rule-Based Storytelling Text-to-Speech (TTS) Synthesis

et al. 2016

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Abstract. In recent years, various real life applications such as talking books, gadgets and humanoid robots have drawn the attention to pursue research in the area of expressive speech synthesis. Speech synthesis is widely used in various applications. However, there is a growing need for an expressive speech synthesis especially for communication and robotic. In this paper, global and local rule are developed to convert neutral to storytelling style speech for the Malay language. In order to generate rules, modification of prosodic parameters such as pitch, intensity, duration, tempo and pauses are considered. Modification of prosodic parameters is examined by performing prosodic analysis on a story collected from an experienced female and male storyteller. The global and local rule is applied in sentence level and synthesized using HNM. Subjective tests are conducted to evaluate the synthesized storytelling speech quality of both rules based on naturalness, intelligibility, and similarity to the original storytelling speech. The results showed that global rule give a better result than local rule

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Expressive speech synthesis: a review

Cited by 50 publications

References 59 publications

Can We Generate Emotional Pronunciations for Expressive Speech Synthesis?

Can We Generate Emotional Pronunciations for Expressive Speech Synthesis?

Developing an Online Self-learning System of Indonesian Pronunciation for Foreign Learners

Rule-Based Storytelling Text-to-Speech (TTS) Synthesis

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