Machine translation evaluation through post-editing measures in audio description

The number of accessible audiovisual products and the pace at which audiovisual content is made accessible need to be increased, reducing costs whenever possible. T he implementation of different technologies which are already available in the translation field, specifically machine translation technologies, could help reach this goal in audio description for the blind and partially sighted. Measuring machine translation quality is essential when selecting the most appropriate machine translation engine to be implemented in the audio description field for the English-Catalan language combination. Automatic metrics and human assessments are often used for this purpose in any specific domain and language pair. T his article proposes a methodology based on both objective and subjective measures for the evaluation of five different and free online machine translation systems. T heir raw machine translation outputs and the post-editing effort that is involved are assessed using eight different scores. Results show that there are clear quality differences among the systems assessed and that one of them is the best rated in six out of the eight evaluation measures used. T his engine would therefore yield the best freely machine-translated audio descriptions in Catalan presumably reducing the audio description process turnaround and costs.