# FOOCTTS: Generating Arabic Speech with Acoustic Environment for Football Commentator

arXiv: https://arxiv.org/abs/2306.07936 · HTML: https://mlsanity.com/paper/2306.07936/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 5 references that are in the map.
- First posted on arXiv 7 Jun 2023.

## Builds on (most cited first, 3 of 3)

- [Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech](https://mlsanity.com/paper/2106.06103/) (2021)
- [QASR: QCRI Aljazeera Speech Resource -- A Large Scale Annotated Arabic Speech Corpus](https://mlsanity.com/paper/2106.13000/) (2021)
- [Unsupervised Data Selection for TTS: Using Arabic Broadcast News as a Case Study](https://mlsanity.com/paper/2301.09099/) (2023)

## Abstract (arXiv)

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.