# Towards cross-language prosody transfer for dialog

arXiv: https://arxiv.org/abs/2307.04123 · HTML: https://mlsanity.com/paper/2307.04123/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 32 references that are in the map.
- First posted on arXiv 9 Jul 2023.

## Builds on (most cited first, 17 of 17)

- [Common Voice: A Massively-Multilingual Speech Corpus](https://mlsanity.com/paper/1912.06670/) (2019)
- [MLS: A Large-Scale Multilingual Dataset for Speech Research](https://mlsanity.com/paper/2012.03411/) (2020)
- [VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation](https://mlsanity.com/paper/2101.00390/) (2021)
- [Direct speech-to-speech translation with discrete units](https://mlsanity.com/paper/2107.05604/) (2021)
- [Textless Speech-to-Speech Translation on Real Data](https://mlsanity.com/paper/2112.08352/) (2021)
- [The Multilingual TEDx Corpus for Speech Recognition and Translation](https://mlsanity.com/paper/2102.01757/) (2021)
- [Translatotron 2: High-quality direct speech-to-speech translation with voice preservation](https://mlsanity.com/paper/2107.08661/) (2021)
- [CVSS Corpus and Massively Multilingual Speech-to-Speech Translation](https://mlsanity.com/paper/2201.03713/) (2022)
- [Enhanced Direct Speech-to-Speech Translation Using Self-supervised Pre-training and Data Augmentation](https://mlsanity.com/paper/2204.02967/) (2022)
- [UWSpeech: Speech to Speech Translation for Unwritten Languages](https://mlsanity.com/paper/2006.07926/) (2020)
- [MaSS: A Large and Clean Multilingual Corpus of Sentence-aligned Spoken Utterances Extracted from the Bible](https://mlsanity.com/paper/1907.12895/) (2019)
- [Leveraging unsupervised and weakly-supervised data to improve direct speech-to-speech translation](https://mlsanity.com/paper/2203.13339/) (2022)
- [Whisper: Fast Flooding for Low-Power Wireless Networks](https://mlsanity.com/paper/1809.03699/) (2018)
- [Unmet Needs and Opportunities for Mobile Translation AI](https://mlsanity.com/paper/2002.12387/) (2020)
- [Leveraging Pseudo-labeled Data to Improve Direct Speech-to-Speech Translation](https://mlsanity.com/paper/2205.08993/) (2022)
- [A Holistic Cascade System, benchmark, and Human Evaluation Protocol for Expressive Speech-to-Speech Translation](https://mlsanity.com/paper/2301.10606/) (2023)
- [Dialogs Re-enacted Across Languages](https://mlsanity.com/paper/2211.11584/) (2022)

## Built on by (most cited first, 5 of 5)

- [EmphAssess : a Prosodic Benchmark on Assessing Emphasis Transfer in Speech-to-Speech Models](https://mlsanity.com/paper/2312.14069/) (2023)
- [A Collection of Pragmatic-Similarity Judgments over Spoken Dialog Utterances](https://mlsanity.com/paper/2403.14808/) (2024)
- [Which Prosodic Features Matter Most for Pragmatics?](https://mlsanity.com/paper/2408.13240/) (2024)
- [Is Prosody Lost in Translation? Fine-Grained Cross-Lingual Prosody Similarity Across Languages](https://mlsanity.com/paper/2608.27848/) (2026)
- [MoVE: Translating Laughter and Tears via Mixture of Vocalization Experts in Speech-to-Speech Translation](https://mlsanity.com/paper/2604.17435/) (2026)

## Abstract (arXiv)

Speech-to-speech translation systems today do not adequately support use for dialog purposes. In particular, nuances of speaker intent and stance can be lost due to improper prosody transfer. We present an exploration of what needs to be done to overcome this. First, we developed a data collection protocol in which bilingual speakers re-enact utterances from an earlier conversation in their other language, and used this to collect an English-Spanish corpus, so far comprising 1871 matched utterance pairs. Second, we developed a simple prosodic dissimilarity metric based on Euclidean distance over a broad set of prosodic features. We then used these to investigate cross-language prosodic differences, measure the likely utility of three simple baseline models, and identify phenomena which will require more powerful modeling. Our findings should inform future research on cross-language prosody and the design of speech-to-speech translation systems capable of effective prosody transfer.