Last Syllable Unit Penalization in Unit Selection TTS

Jůzová, Markéta; Tihelka, Daniel; Skarnitzl, Radek

doi:10.1007/978-3-319-64206-2_36

Cited by 9 publications

(5 citation statements)

References 29 publications

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“…The final comparison of the evaluation experiment using sentences of the speech corpus SC1 with the results obtained by the standard listening test method described in more detail in [11] shows principal correspondence as documented by the graphs in Figure 11. While the results for the M1, F1, and M2 voices are stable and prefer the TTS 2 method for both databases, for the F2 voice the results are classified as similar in the TTS 1 as well as the TTS 2 .…”

Section: Discussion Of the Obtained Resultsmentioning

confidence: 63%

“…To evaluate synthetic speech quality by continual classification in the P-A scale, we collected the first speech corpus (SC1) consisting of three parts: the original speech uttered by real speakers, and two variations of speech synthesis produced by the Czech TTS system using the USEL method [16] with voices based on the original speaker. Two methods of prosody manipulation were applied: the rule-based method (assigned as TTS A ) and the modified version reflecting the final syllable status (as TTS B ) [11]. The natural as well as the synthetic speech originates from four professional speakers-two males (M1, M2) and two females (F1, F2).…”

Section: Materials Used Initial Settings and Conditionsmentioning

confidence: 99%

“…Twenty-two evaluators (of which seven were speech synthesis experts, six were phoneticians and nine were naive listeners) participated in this subjective listening test experiment. The evaluation carried out is described in more detail in [11]. The final results of the automatic evaluation system based on the GMM classification in the P-A space are compared visually with the evaluation results of the standard listening tests in the bar-graphs in Figure 11.…”

Section: Review 12 Of 19mentioning

confidence: 99%

“…The listening test evaluations were carried out previously between the years 2017 and 2019 for different research purposes [11,17]. In both of the tests, the order of the utterances was randomized in each of the ten sets so that the synthesis method was not known to the listener in advance.…”

Section: Review 12 Of 19mentioning

confidence: 99%

“…Within the framework of the work presented, two basic evaluation experiments with the Czech speech synthesizer of male and female voices were performed. The first was aimed at the evaluation of sentences generated by the TTS system using two methods of prosody manipulation-a rule-based method and a modification reflecting the final syllable status [11]. The second compared the differences between the tested sentences produced by the TTS system using three different synthesis methods (standard and deep learning [12,13]) in combination with rule-based prosody generation.…”

Section: Introductionmentioning

confidence: 99%

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GMM-Based Evaluation of Synthetic Speech Quality Using 2D Classification in Pleasure-Arousal Scale

Přibil

Přibilová

Matoušek³

2020

Applied Sciences

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The paper focuses on the description of a system for the automatic evaluation of synthetic speech quality based on the Gaussian mixture model (GMM) classifier. The speech material originating from a real speaker is compared with synthesized material to determine similarities or differences between them. The final evaluation order is determined by distances in the Pleasure-Arousal (P-A) space between the original and synthetic speech using different synthesis and/or prosody manipulation methods implemented in the Czech text-to-speech system. The GMM models for continual 2D detection of P-A classes are trained using the sound/speech material from the databases without any relation to the original speech or the synthesized sentences. Preliminary and auxiliary analyses show a substantial influence of the number of mixtures, the number and type of the speech features used the size of the processed speech material, as well as the type of the database used for the creation of the GMMs on the P-A classification process and on the final evaluation result. The main evaluation experiments confirm the functionality of the system developed. The objective evaluation results obtained are principally correlated with the subjective ratings of human evaluators; however, partial differences were indicated, so a subsequent detailed investigation must be performed.

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Section: Discussion Of the Obtained Resultsmentioning

confidence: 63%

Section: Materials Used Initial Settings and Conditionsmentioning

confidence: 99%

Section: Review 12 Of 19mentioning

confidence: 99%

Section: Review 12 Of 19mentioning

confidence: 99%