Abstract

Context: Real-time speech translation technology is today available but still lacks a complete understanding of how such technology may affect communication in global software projects. Goal: To investigate the adoption of combining speech recognition and machine translation in order to overcome language barriers among stakeholders who are remotely negotiating software requirements. Method: We performed an empirical simulation-based study including: Google Web Speech API and Google Translate service, two groups of four subjects, speaking Italian and Brazilian Portuguese, and a test set of 60 technical and non-technical utterances. Results: Our findings revealed that, overall: (i) a satisfactory accuracy in terms of speech recognition was achieved, although significantly affected by speaker and utterance differences; (ii) adequate translations tend to follow accurate transcripts, meaning that speech recognition is the most critical part for speech translation technology. Conclusions: Results provide a positive albeit initial evidence towards the possibility to use speech translation technologies to help globally distributed team members to communicate in their native languages.

Autore Pugliese

• Calefato Fabio , Lanubile Filippo

Tutti gli autori

• CALEFATO F.;LANUBILE F.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2014

ISSN

Non Disponibile

ISBN

978-1-4503-2774-9

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

2

Ultimo Aggiornamento Citazioni

Non Disponibile

Settori ERC

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Codici ASJC

Non Disponibile