Assessing the quality of TTS audio in the LARA learning-by-reading platform

Elham Akhlaghi, Anna Bączkowska, Harald Berthelsen, Branislav Bédi, Cathy Chua, Catia Cucchiarini, Hanieh Habibi, Ivana Horváthová, Pernille Hvalsøe, Roy Lotz, Christele Maizonniaux, Neasa Ní Chiaráin, Manny Rayner, Nikos Tsourakis, Chunlin Yao

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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A popular idea in Computer Assisted Language Learning (CALL) is to use multimodal annotated texts, with annotations typically including embedded audio and translations, to support L2 learning through reading. An important question is how to create the audio, which can be done either through human recording or by a Text-To-Speech (TTS) synthesis engine. We may reasonably expect TTS to be quicker and easier, but humans to be of higher quality. Here, we report a study using the open-source LARA platform and ten languages. Samples of LARA audio totaling about three and a half minutes were provided for each language in both human and TTS form; subjects used a web form to compare different versions of the same item and rate the voices as a whole. Although human voice was more often preferred, TTS achieved higher ratings in some languages and was close in others.
Original languageEnglish
Title of host publicationCALL and professionalisation
Subtitle of host publicationshort papers from EUROCALL 2021
EditorsNaouel Zoghlami, Cédric Brudermann, Cedric Sarré, Muriel Grosbois, Linda Bradley, Sylvie Thouësny
Place of PublicationFrance
Number of pages5
ISBN (Electronic)9782490057979
Publication statusPublished - Dec 2021
EventEUROCALL 2021: CALL & Professionalisation - Online conference
Duration: 26 Aug 202127 Aug 2021


ConferenceEUROCALL 2021
CityOnline conference
Internet address


  • Reading
  • Multimodality
  • Text-To-Speech (TTS)
  • Evaluation


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