Cross-correlations Between EMA and RIP Signals by Distance and Sentence Type

Cross-correlations between Electromagnetic Articulography (EMA) and Respiratory Inductance Plethysmography (RIP) signals, analyzed by distinct EMA distance measures and sentence type. The dataset is 5.5 KB in size and was authored by Tabea Thies, last updated on 2026-05-28. It is shared under a CC-BY-4.0 license on figshare.

Use Cases

• Analyze the correlation between articulatory movements and breathing patterns based on EMA and RIP signals.
• Compare speech production dynamics across different sentence types based on the described sentence type variable.
• Investigate the effect of different distance measures on observed correlations between EMA and RIP data.

Strengths

• Dataset is small (5.5 KB), facilitating quick download and initial exploration.
• Explicitly licensed as CC-BY-4.0, allowing for broad reuse with attribution.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.

Provenance

Source

figshare

Freshness

Last updated 2026-05-28 17:25:55; freshness should be verified.