Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
FPETS: Fully Parallel End-to-End Text-to-Speech System
Authors: Dabiao Ma, Zhiba Su, Wenxuan Wang, Yuhao Lu8457-8463
AAAI 2020 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results show FPETS utilizes the power of parallel computation and reaches a significant speed up of inference compared with state-of-the-art end-to-end TTS systems. |
| Researcher Affiliation | Collaboration | 1Turing Robot Co.,Ltd. Beijing, China EMAIL 2The Chinese University of Hong Kong, Shenzhen. Guangdong, China EMAIL |
| Pseudocode | No | The paper describes the model architecture and training strategy in text and diagrams, but does not include structured pseudocode or algorithm blocks. |
| Open Source Code | No | Codes and demos will be released at https://github.com/ suzhiba/Full-parallel 100x real time End2End TTS |
| Open Datasets | Yes | LJ speech(Ito 2017) is a public speech dataset consisting of 13100 pairs of text and 22050 HZ audio clips. |
| Dataset Splits | No | The paper mentions using LJ speech dataset and various evaluation sets (Harvard Sentences, 100 random sentences), but it does not provide specific training/validation/test splits for the main dataset to reproduce the data partitioning. |
| Hardware Specification | Yes | All the experiments are done on 4 GTX 1080Ti GPUs |
| Software Dependencies | No | The paper mentions using Adam optimizer with specific parameters, but does not provide specific software dependencies like programming languages, libraries, or frameworks with version numbers. |
| Experiment Setup | Yes | Hyperparameters of our model are showed in Table 1. ... Each model is trained 300k steps. All the experiments are done on 4 GTX 1080Ti GPUs, with batch size of 32 sentences on each GPU. |