@inproceedings{popescu-belis-etal-2025-speech,
title = "Speech-to-Speech Translation Pipelines for Conversations in Low-Resource Languages",
author = "Popescu-Belis, Andrei and
Allemann, Alexis and
Ferrari, Teo and
Krishnamani, Gopal",
editor = {Bouillon, Pierrette and
Gerlach, Johanna and
Girletti, Sabrina and
Volkart, Lise and
Rubino, Raphael and
Sennrich, Rico and
L{\"a}ubli, Samuel and
Volk, Martin and
Espl{\`a}-Gomis, Miquel and
Vandeghinste, Vincent and
Moniz, Helena and
Szoc, Sara},
booktitle = "Proceedings of Machine Translation Summit XX: Volume 2",
month = jun,
year = "2025",
address = "Geneva, Switzerland",
publisher = "European Association for Machine Translation",
url = "https://aclanthology.org/2025.mtsummit-2.3/",
pages = "18--27",
ISBN = "978-2-9701897-1-8",
abstract = "The popularity of automatic speech-to-speech translation for human conversations is growing, but the quality varies significantly depending on the language pair. In a context of community interpreting for low-resource languages, namely Turkish and Pashto to/from French, we collected fine-tuning and testing data, and compared systems using several automatic metrics (BLEU, COMET, and BLASER) and human assessments. The pipelines consist of automatic speech recognition, machine translation, and speech synthesis, with local models and cloud-based commercial ones. Some components have been fine-tuned on our data. We evaluated over 60 pipelines and determined the best one for each direction. We also found that the ranks of components are generally independent of the rest of the pipeline."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="popescu-belis-etal-2025-speech">
<titleInfo>
<title>Speech-to-Speech Translation Pipelines for Conversations in Low-Resource Languages</title>
</titleInfo>
<name type="personal">
<namePart type="given">Andrei</namePart>
<namePart type="family">Popescu-Belis</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alexis</namePart>
<namePart type="family">Allemann</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Teo</namePart>
<namePart type="family">Ferrari</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Gopal</namePart>
<namePart type="family">Krishnamani</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2025-06</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of Machine Translation Summit XX: Volume 2</title>
</titleInfo>
<name type="personal">
<namePart type="given">Pierrette</namePart>
<namePart type="family">Bouillon</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Johanna</namePart>
<namePart type="family">Gerlach</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Sabrina</namePart>
<namePart type="family">Girletti</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Lise</namePart>
<namePart type="family">Volkart</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Raphael</namePart>
<namePart type="family">Rubino</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Rico</namePart>
<namePart type="family">Sennrich</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Samuel</namePart>
<namePart type="family">Läubli</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Martin</namePart>
<namePart type="family">Volk</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Miquel</namePart>
<namePart type="family">Esplà-Gomis</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Vincent</namePart>
<namePart type="family">Vandeghinste</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Helena</namePart>
<namePart type="family">Moniz</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Sara</namePart>
<namePart type="family">Szoc</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>European Association for Machine Translation</publisher>
<place>
<placeTerm type="text">Geneva, Switzerland</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">978-2-9701897-1-8</identifier>
</relatedItem>
<abstract>The popularity of automatic speech-to-speech translation for human conversations is growing, but the quality varies significantly depending on the language pair. In a context of community interpreting for low-resource languages, namely Turkish and Pashto to/from French, we collected fine-tuning and testing data, and compared systems using several automatic metrics (BLEU, COMET, and BLASER) and human assessments. The pipelines consist of automatic speech recognition, machine translation, and speech synthesis, with local models and cloud-based commercial ones. Some components have been fine-tuned on our data. We evaluated over 60 pipelines and determined the best one for each direction. We also found that the ranks of components are generally independent of the rest of the pipeline.</abstract>
<identifier type="citekey">popescu-belis-etal-2025-speech</identifier>
<location>
<url>https://aclanthology.org/2025.mtsummit-2.3/</url>
</location>
<part>
<date>2025-06</date>
<extent unit="page">
<start>18</start>
<end>27</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Speech-to-Speech Translation Pipelines for Conversations in Low-Resource Languages
%A Popescu-Belis, Andrei
%A Allemann, Alexis
%A Ferrari, Teo
%A Krishnamani, Gopal
%Y Bouillon, Pierrette
%Y Gerlach, Johanna
%Y Girletti, Sabrina
%Y Volkart, Lise
%Y Rubino, Raphael
%Y Sennrich, Rico
%Y Läubli, Samuel
%Y Volk, Martin
%Y Esplà-Gomis, Miquel
%Y Vandeghinste, Vincent
%Y Moniz, Helena
%Y Szoc, Sara
%S Proceedings of Machine Translation Summit XX: Volume 2
%D 2025
%8 June
%I European Association for Machine Translation
%C Geneva, Switzerland
%@ 978-2-9701897-1-8
%F popescu-belis-etal-2025-speech
%X The popularity of automatic speech-to-speech translation for human conversations is growing, but the quality varies significantly depending on the language pair. In a context of community interpreting for low-resource languages, namely Turkish and Pashto to/from French, we collected fine-tuning and testing data, and compared systems using several automatic metrics (BLEU, COMET, and BLASER) and human assessments. The pipelines consist of automatic speech recognition, machine translation, and speech synthesis, with local models and cloud-based commercial ones. Some components have been fine-tuned on our data. We evaluated over 60 pipelines and determined the best one for each direction. We also found that the ranks of components are generally independent of the rest of the pipeline.
%U https://aclanthology.org/2025.mtsummit-2.3/
%P 18-27
Markdown (Informal)
[Speech-to-Speech Translation Pipelines for Conversations in Low-Resource Languages](https://aclanthology.org/2025.mtsummit-2.3/) (Popescu-Belis et al., MTSummit 2025)
ACL