Should Corpora be Big, Rich, or Dense?

TL;DR

This paper examines the qualities that make large speech corpora useful, emphasizing that size alone isn't sufficient and exploring how multi-channel data can enhance analysis despite smaller scale.

Contribution

It challenges the focus on corpus size by highlighting the importance of rich variation and introduces multi-channel data as a means to improve speech analysis.

Findings

Large corpora offer statistical stability and variation.

Multi-channel data can provide detailed speech production insights.

Size alone doesn't determine corpus usefulness.

Abstract

In this paper, we ask what properties makes a large corpus more or less useful. We suggest that size, by itself, should not be the ultimate goal of building a corpus. Large-scale corpora are considered desirable because they offer statistical stability and rich variation. But this rich variation means more factors to control and evaluate, which can limit the advantages of size. We discuss the use of multi-channel data to complement large-scale speech corpora. Even though multi-channel data may limit the scale of a corpus (due to the complex and labor-intensive nature of data collection) they can offer information that allows us to tease apart various factors related to speech production.