AUTOMATIC PROSODY GENERATION BY NEURAL-STATISTICAL HYBRID MODEL FOR UNIT SELECTION SPEECH SYNTHESIS

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SHEYKHAN M.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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Journal: IRANIAN JOURNAL OF BIOMEDICAL ENGINEERING Year:2007 | Volume:1 | Issue:3 Page(s): 227-240

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Title

AUTOMATIC PROSODY GENERATION BY NEURAL-STATISTICAL HYBRID MODEL FOR UNIT SELECTION SPEECH SYNTHESIS

Author(s)

SHEYKHAN M. | Issue Writer Certificate

Keywords

PROSODYQ3

PITCH CONTOURQ3

DURATIONQ3

RECURRENT NEURAL NETWORKQ3

DECISION TREEQ3

GAUSSIAN MIXTURE MODELQ3

SPEECH SYNTHESISQ3

UNIT SELECTIONQ3

SYLLABLEQ3

Abstract

In the first version of our Farsi Text-To-Speech (TTS) system, a RECURRENT NEURAL NETWORK (RNN) was used to generate PROSODY parameters (pitch contour, DURATION, energy and pause), and a Harmonic + Noise Model (HNM) speech synthesizer was used to concatenate the single units of diphones. To improve the performance of TTS, in this paper, two modifications are presented. In the first one is a neural-statistical hybrid model in which RNN plays the role of PROSODY parameterizer and the combination of DECISION TREEs and GAUSSIAN MIXTURE MODELs (GMMs) gives the probability distributions of targets and transitions in each context a equivalent cluster. Another modification is about developing a UNIT SELECTION speech synthesizer in which SYLLABLE is selected as the basic synthesis unit and, due to the first modification, an effective UNIT SELECTION strategy is also conducted. To evaluate the performance of the system, the rating scales presented in the recommendation P.85 of the International Telecommunication Union (ITU) were used and the Mean Opinion Score (MOS) over six scales was achieved as 3.6.

Cites

References

DESIGN AND IMPLEMENTATION OF A TEXT TO SPEECH SYSTEM FOR FARSI LANGUAGE

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APA: Copy

SHEYKHAN, M.. (2007). AUTOMATIC PROSODY GENERATION BY NEURAL-STATISTICAL HYBRID MODEL FOR UNIT SELECTION SPEECH SYNTHESIS. IRANIAN JOURNAL OF BIOMEDICAL ENGINEERING, 1(3), 227-240. SID. https://sid.ir/paper/81640/en

Vancouver: Copy

SHEYKHAN M.. AUTOMATIC PROSODY GENERATION BY NEURAL-STATISTICAL HYBRID MODEL FOR UNIT SELECTION SPEECH SYNTHESIS. IRANIAN JOURNAL OF BIOMEDICAL ENGINEERING[Internet]. 2007;1(3):227-240. Available from: https://sid.ir/paper/81640/en

IEEE: Copy

M. SHEYKHAN, “AUTOMATIC PROSODY GENERATION BY NEURAL-STATISTICAL HYBRID MODEL FOR UNIT SELECTION SPEECH SYNTHESIS,” IRANIAN JOURNAL OF BIOMEDICAL ENGINEERING, vol. 1, no. 3, pp. 227–240, 2007, [Online]. Available: https://sid.ir/paper/81640/en

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