Fluent personalized speech synthesis with prosodic word-level spontaneous speech generation

2015 ◽  
Author(s):  
Yi-Chin Huang ◽  
Chung-Hsien Wu ◽  
Ming-Ge Shie
Keyword(s):  
Speech Synthesis ◽  
Spontaneous Speech ◽  
Prosodic Word ◽  
Word Level ◽  
Speech Generation

Toward Spontaneous Speech Synthesis—Utilizing Language Model Information in TTS

2004 ◽  
Vol 12 (4) ◽  
pp. 436-445 ◽  
Author(s):  
S. Werner ◽  
M. Eichner ◽  
M. Wolff ◽  
R. Hoffmann
Keyword(s):  
Speech Synthesis ◽  
Language Model ◽  
Spontaneous Speech

Toward hidden Markov model‐based spontaneous speech synthesis

2006 ◽  
Vol 120 (5) ◽  
pp. 3037-3038
Author(s):  
Tatsuya Akagawa ◽  
Koji Iwano ◽  
Sadaoki Furui
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Speech Synthesis ◽  
Hidden Markov ◽  
Spontaneous Speech ◽  
Model Based

scholarly journals In which Clause do Subordinate Conjunctions Prosodically Belong?

2019 ◽  
Vol 70 (2) ◽  
pp. 216-224
Author(s):  
Zuzana Komrsková ◽  
Petra Poukarová
Keyword(s):  
Spontaneous Speech ◽  
Subordinate Clause ◽  
Prosodic Word ◽  
Functional Differences

Abstract This paper deals with the position of three Czech subordinating conjunctions že ’that’, když ‘when’, and až ‘when’ within the prosodic word, using the phonetic annotation in the ORTOFON corpus. The position of subordinating conjunctions is traditionally described as initial within the subordinate clause, but the situation in spontaneous speech is not so clear. This paper shows the functional differences between the various positions within the prosodic word and presents the words which are most frequently combined with the selected conjunctions.

scholarly journals Word-Level Style Control for Expressive, Non-attentive Speech Synthesis

2021 ◽  
pp. 336-347
Author(s):  
Konstantinos Klapsas ◽  
Nikolaos Ellinas ◽  
June Sig Sung ◽  
Hyoungmin Park ◽  
Spyros Raptis
Keyword(s):  
Speech Synthesis ◽  
Word Level

Error Free Punjabi Text to Speech Generation System based on Phonemes

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.

Perception of smiling voice in spontaneous speech synthesis

2021 ◽  
Author(s):  
Ambika Kirkland ◽  
Marcin Włodarczak ◽  
Joakim Gustafson ◽  
Eva Szekely
Keyword(s):  
Speech Synthesis ◽  
Spontaneous Speech
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