Speech Rate Calculations with Short Utterances: A Study from a Speech-to-Speech, Machine Translation Mediated Map Task
Akira Hayakawa | Carl Vogel | Saturnino Luz | Nick Campbell
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)
The ILMT-s2s Corpus ― A Multimodal Interlingual Map Task Corpus
Akira Hayakawa | Saturnino Luz | Loredana Cerrato | Nick Campbell
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
This paper presents the multimodal Interlingual Map Task Corpus (ILMT-s2s corpus) collected at Trinity College Dublin, and discuss some of the issues related to the collection and analysis of the data. The corpus design is inspired by the HCRC Map Task Corpus which was initially designed to support the investigation of linguistic phenomena, and has been the focus of a variety of studies of communicative behaviour. The simplicity of the task, and the complexity of phenomena it can elicit, make the map task an ideal object of study. Although there are studies that used replications of the map task to investigate communication in computer mediated tasks, this ILMT-s2s corpus is, to the best of our knowledge, the first investigation of communicative behaviour in the presence of three additional “filters”: Automatic Speech Recognition (ASR), Machine Translation (MT) and Text To Speech (TTS) synthesis, where the instruction giver and the instruction follower speak different languages. This paper details the data collection setup and completed annotation of the ILMT-s2s corpus, and outlines preliminary results obtained from the data.