FOOCTTS: Generating Arabic Speech with Acoustic Environment for Football Commentator
This paper presents FOOCTTS, an automatic pipeline for a football commentator that generates speech with background crowd noise. The application gets the text from the user, applies text pre-processing such as vowelization, followed by the commentator's speech synthesizer. Our pipeline included Arabic automatic speech recognition for data labeling, CTC segmentation, transcription vowelization to match speech, and fine-tuning the TTS. Our system is capable of generating speech with its acoustic environment within limited 15 minutes of football commentator recording. Our prototype is generalizable and can be easily applied to different domains and languages.
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Methods
1x1 Convolution •
Adam •
Batch Normalization •
BigGAN •
Conditional Batch Normalization •
Convolution •
Dense Connections •
Dot-Product Attention •
Early Stopping •
Feedforward Network •
GAN Hinge Loss •
Linear Layer •
Non-Local Block •
Non-Local Operation •
Off-Diagonal Orthogonal Regularization •
Projection Discriminator •
ReLU •
Residual Block •
Residual Connection •
SAGAN •
SAGAN Self-Attention Module •
Softmax •
Spectral Normalization •
Truncation Trick •
TTUR
