An NLP Based Text-to-Speech Synthesizer for Moroccan Arabic

The success of social robotics is directly linked to their ability of interacting with people. Humans possess verbal and non-verbal communication skills, and, therefore, both are essential for social robots to get a natural human–robot interaction. This work focuses on the first of them since the majority of social robots implement an interaction system endowed with verbal capacities. In order to do this implementation, we must equip social robots with an artificial voice system. In robotics, a Text to Speech (TTS) system is the most common speech synthesizer technique. The performance of a speech synthesizer is mainly evaluated by its similarity to the human voice in relation to its intelligibility and expressiveness. In this paper, we present a comparative study of eight off-the-shelf TTS systems used in social robots. In order to carry out the study, 125 participants evaluated the performance of the following TTS systems: Google, Microsoft, Ivona, Loquendo, Espeak, Pico, AT&T, and Nuance. The evaluation was performed after observing videos where a social robot communicates verbally using one TTS system. The participants completed a questionnaire to rate each TTS system in relation to four features: intelligibility, expressiveness, artificiality, and suitability. In this study, four research questions were posed to determine whether it is possible to present a ranking of TTS systems in relation to each evaluated feature, or, on the contrary, there are no significant differences between them. Our study shows that participants found differences between the TTS systems evaluated in terms of intelligibility, expressiveness, and artificiality. The experiments also indicated that there was a relationship between the physical appearance of the robots (embodiment) and the suitability of TTS systems.

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Error Free Punjabi Text to Speech Generation System based on Phonemes

International Journal of Emerging Research in Management and Technology ◽

10.23956/ijermt.v6i8.134 ◽

2018 ◽

Vol 6 (8) ◽

pp. 172

Author(s):

Tejinder Kaur ◽

Charanjiv Singh

Keyword(s):

Computer System ◽

Distinctive Feature ◽

Speech Signal ◽

Speech Synthesis ◽

Euclidean Distance ◽

Previous Method ◽

Text To Speech ◽

Generation System ◽

Speech Synthesizer ◽

Speech Generation

Text-to-speech (TTS) is the generation ofsynthesized speech from text.Language is the ability to express one’sthoughts by means of a set of signs (text), gestures,and sounds. It is a distinctive feature of humanbeings, who are the only creatures to use such asystem. Speech is the oldest means of communicationbetween people and it is also the most widely used.‘Speech synthesis’ also called ‘Text to speechsynthesis’ is the artificial production ofhuman speech. A computer system used for thispurpose is called a speech synthesizer and can beimplemented in software. A text-to-speech(TTS) system converts text to speech.The proposed Enhanced Transcriptions Method is developed using Microsoft Visual Studio in VB.Net Language. Firstly word indexing is performed for the predefined words then corresponding speech signal is detected and errors in words are calculated using Euclidean distance. The results of the proposed work shows that Enhanced Transcriptions Method has more accuracy 89% as compared to previous Transcriptions Method 79%. The value of specificity for proposed method is 0.89 and for previous method is 0.79.

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