Dataset supporting the publication "Improved tactile speech robustness to background noise with a dual-path recurrent neural network noise-reduction method"

This dataset supports the publication:
Fletcher, M., Perry, S., Thoidis, I., Verschuur, C., & Goehring, T. (2024). Improved tactile speech robustness to background noise with a dual-path recurrent neural network noise-reduction method. Scientific Reports.

This dataset contains three CSV files: one for the objective assessment of the audio, one for the objective assessment of the tactile signal, and one for the behavioural assessment.

The objective audio CSV file shows the eSTOI and SI-SDR scores for each model at each of the SNRs tested for the four different noise reduction methods and with no noise reduction. Data is shown for the Party noise and ITASS noise.

The objective tactile CSV file shows the SI-SDR scores for each model at each of the SNRs tested for the four different noise reduction methods and with no noise reduction. Rows show different sentences. Column headings stat the processing applied (no processing, log-MMSE, or DPRNN methods), the SNR, and whether the data is for the male ("M") or female ("F") talker.

The behavioural CSV file shows the participant number (matching the number used for the data presented in the published article associated with this dataset), dominant hand (left/right), wrist height, width, and circumference (mm), 31.5 Hz threshold and 125 Hz vibro-tactile detection threshold at the fingertip (ms/2), wrist temperature (0C), gender, age, and percentage correct for sentence identification in each condition. The header name for each condition shows whether or not noise reduction ("NR") was applied, the SNR, and whether the talker was male or female.

All data was collected at the University of Southampton, U.K.