Title
Human-machine performances in interlingual live subtitling with different "Englishes"
Conference name
Media for All 10 Conference
City
Country
Belgium
Modalities
Date
06/07/2023-07/07/2023
Abstract
Live subtitling (LS) finds its foundations in subtitling for the d/Deaf and Hard of Hearing, i.e. the need to produce subtitles from and to the same language with specific audio features (intralingual), and from oral into written content (intersemiotic). The interlingual variation of LS, referred to as Interlingual Live Subtitling (ILS), combines all this with the urgency of guaranteeing multilingual accessibility (interlingual) to provide full accessibility for all.
Situated at the crossroads between Audio-visual Translation (AVT) and Simultaneous Interpreting (SI), ILS draws on both human-mediated translation and automatic language processing systems and it is currently being achieved by using different approaches and techniques, each of them requiring different degrees of human-machine interaction (HMI). One of the more human oriented ILS modes this research focuses on is interlingual respeaking, via Automatic Speech Recognition (ASR), and the combination of intra and interlingual respeaking and SI as currently used workflows to create real-time subtitles at live events.
The proposal aims at presenting a new case study developed following the results from a Doctoral research by the University of Genoa, Italy (Pagano, 2022) and other two parallel studies (Dawson, 2021; Romero-Fresco & Alonso-Bacigalupe, 2022) on five different ILS workflows pointing out their strengths and weaknesses.
This follow-up case study tests and compares the same five ILS methods from English to Italian on a scale with different degrees of HMI: interlingual respeaking, simultaneous interpreting + intralingual respeaking, and simultaneous interpreting + ASR being more subject to human agency in terms of input, editing and review of the transcription, while in the last two – intralingual respeaking + Machine Translation (MT), and the fully-automatic ASR + MT – the final say is given to machines, without any human monitoring. Four SI students were involved in the study and trained in intra and interlingual respeaking to perform with different roles in one source video of a real-life speech in English given by a foreign speaker. The final outputs for each of the five methods are assessed concerning linguistic accuracy and delay. Analyses are carried out drawing upon the word-based NTR Model calculation (Romero-Fresco & Pöchhacker, 2017) together with a more conceptual and semantic-oriented level of analysis, and calculating the synchronicity of the subtitles – how many seconds it takes for their broadcasting.
In addition, the speeches used in the study are delivered in English by EFL speakers, using more of a Globish language, English as a lingua franca which is not always well pronounced and articulated as one by mother tongues. In this particular but at the same time more and more common situation of speech delivery in public speaking, it is hoped that the contribution can induce further reflection on the importance of human interaction with machine systems in providing high quality media accessibility for live events, when EFL speakers are involved.
Situated at the crossroads between Audio-visual Translation (AVT) and Simultaneous Interpreting (SI), ILS draws on both human-mediated translation and automatic language processing systems and it is currently being achieved by using different approaches and techniques, each of them requiring different degrees of human-machine interaction (HMI). One of the more human oriented ILS modes this research focuses on is interlingual respeaking, via Automatic Speech Recognition (ASR), and the combination of intra and interlingual respeaking and SI as currently used workflows to create real-time subtitles at live events.
The proposal aims at presenting a new case study developed following the results from a Doctoral research by the University of Genoa, Italy (Pagano, 2022) and other two parallel studies (Dawson, 2021; Romero-Fresco & Alonso-Bacigalupe, 2022) on five different ILS workflows pointing out their strengths and weaknesses.
This follow-up case study tests and compares the same five ILS methods from English to Italian on a scale with different degrees of HMI: interlingual respeaking, simultaneous interpreting + intralingual respeaking, and simultaneous interpreting + ASR being more subject to human agency in terms of input, editing and review of the transcription, while in the last two – intralingual respeaking + Machine Translation (MT), and the fully-automatic ASR + MT – the final say is given to machines, without any human monitoring. Four SI students were involved in the study and trained in intra and interlingual respeaking to perform with different roles in one source video of a real-life speech in English given by a foreign speaker. The final outputs for each of the five methods are assessed concerning linguistic accuracy and delay. Analyses are carried out drawing upon the word-based NTR Model calculation (Romero-Fresco & Pöchhacker, 2017) together with a more conceptual and semantic-oriented level of analysis, and calculating the synchronicity of the subtitles – how many seconds it takes for their broadcasting.
In addition, the speeches used in the study are delivered in English by EFL speakers, using more of a Globish language, English as a lingua franca which is not always well pronounced and articulated as one by mother tongues. In this particular but at the same time more and more common situation of speech delivery in public speaking, it is hoped that the contribution can induce further reflection on the importance of human interaction with machine systems in providing high quality media accessibility for live events, when EFL speakers are involved.