This repository serves as a curated collection of resources for simultaneous translation research, targeting researchers and developers in the field. It provides a comprehensive list of papers, toolkits, datasets, and tutorials to facilitate advancements in real-time text-to-text and speech-to-text translation.

How It Works

The project acts as a central hub, aggregating and organizing key components of simultaneous translation research. It highlights established toolkits like Fairseq and SimulEval, lists conventional and specialized datasets (e.g., IWSLT, WMT, MuST-C, BSTC), and provides links to seminal papers and tutorials covering various aspects from foundational concepts to advanced neural network architectures and evaluation frameworks.

Quick Start & Requirements

This repository is a curated list and does not have a direct installation or execution command. Users will need to refer to the individual toolkits and datasets linked within the README for setup and usage.

Highlighted Details

• Extensive paper list organized by year and category, covering research from 2002 to the present.
• Links to key toolkits: Fairseq for sequence modeling and SimulEval for evaluation.
• Includes a variety of datasets for text-to-text, speech-to-text, and speech-to-speech translation.
• Provides links to tutorials and talks from major NLP conferences.

Maintenance & Community

The repository is maintained by Shaolei Zhang, a Ph.D. student at the Institute of Computing Technology, Chinese Academy of Sciences. The README indicates it is "continuously updating" and encourages contributions and suggestions via email.

Licensing & Compatibility

The repository itself is a collection of links and does not specify a license. Users must adhere to the licenses of the individual toolkits and datasets they choose to use.

Limitations & Caveats

This is a curated list of resources, not a runnable system. Users are responsible for obtaining, installing, and configuring the individual toolkits and datasets. The quality and availability of linked resources may vary.