# Advancing Speech Translation: A Corpus of Mandarin-English Conversational Telephone Speech

arXiv: https://arxiv.org/abs/2404.11619 · HTML: https://mlsanity.com/paper/2404.11619/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 7 references that are in the map.
- First posted on arXiv 25 Mar 2024.

## Builds on (most cited first, 1 of 1)

- [No Language Left Behind: Scaling Human-Centered Machine Translation](https://mlsanity.com/paper/2207.04672/) (2022)

## Built on by (most cited first, 2 of 2)

- [HENT-SRT: Hierarchical Efficient Neural Transducer with Self-Distillation for Joint Speech Recognition and Translation](https://mlsanity.com/paper/2506.02157/) (2025)
- [Whisper-UT: A Unified Translation Framework for Speech and Text](https://mlsanity.com/paper/2509.16375/) (2025)

## Abstract (arXiv)

This paper introduces a set of English translations for a 123-hour subset of the CallHome Mandarin Chinese data and the HKUST Mandarin Telephone Speech data for the task of speech translation. Paired source-language speech and target-language text is essential for training end-to-end speech translation systems and can provide substantial performance improvements for cascaded systems as well, relative to training on more widely available text data sets. We demonstrate that fine-tuning a general-purpose translation model to our Mandarin-English conversational telephone speech training set improves target-domain BLEU by more than 8 points, highlighting the importance of matched training data.