SMALLWorlds – Multilingual Content-Controlled Monologues

13833

Authors

nan

Abstract

AbstractWe present the speech corpus SMALLWorlds (Spoken Multi-lingual Accounts of Logically Limited Worlds), newly established and still growing. SMALLWorlds contains monologic descriptions of scenes or worlds which are simple enough to be formally describable. The descriptions are instances of content-controlled monologue: semantically """"pre-specified"""" but still bearing most hallmarks of spontaneous speech (hesitations and filled pauses, relaxed syntax, repetitions, self-corrections, incomplete constituents, irrelevant or redundant information, etc.) as well as idiosyncratic speaker traits. In the paper, we discuss the pros and cons of data so elicited. Following that, we present a typical SMALLWorlds task: the description of a simple drawing with differently coloured circles, squares, and triangles, with no hints given as to which description strategy or language style to use. We conclude with an example on how SMALLWorlds may be used: unsupervised lexical learning from phonetic transcription. At the time of writing, SMALLWorlds consists of more than 250 recordings in a wide range of typologically diverse languages from many parts of the world, some unwritten and endangered.

Keywords

nan

Full Content

nan

Labeled Text

AbstractWe present the speech corpus SMALLWorlds (Spoken Multi-lingual Accounts of Logically Limited Worlds), newly established and still growing. SMALLWorlds contains monologic descriptions of scenes or worlds which are simple enough to be formally describable. The descriptions are instances of content-controlled monologue: semantically """"pre-specified"""" but still bearing most hallmarks of spontaneous speech (hesitations and filled pauses, relaxed syntax, repetitions, self-corrections, incomplete constituents, irrelevant or redundant information, etc.) as well as idiosyncratic speaker traits. In the paper, we discuss the pros and cons of data so elicited. Following that, we present a typical SMALLWorlds task: the description of a simple drawing with differently coloured circles, squares, and triangles, with no hints given as to which description strategy or language style to use. We conclude with an example on how SMALLWorlds may be used: unsupervised lexical learning from phonetic transcription. At the time of writing, SMALLWorlds consists of more than 250 recordings in a wide range of typologically diverse languages from many parts of the world, some unwritten and endangered.

Publication Details

Paper ID:
13833
Year:
2012
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan