Update README.md

README.md

@@ -22,7 +22,7 @@ Part of MONSTER: <https://arxiv.org/abs/2502.15122>.
 |License|Public Domain|
 |Citations|[1] [2]|
 
-***MosquitoSound***, taken from the broader UCR archive, consists of 279,566 (univariate) time series, each of length 3,750, representing recordings of wingbeats for six different species of mosquito [1, 2]. The task is to identify the species of mosquito based on the recordings. This version of the dataset has been split into stratified random cross-validation folds.
+***MosquitoSound***, taken from the broader UCR archive, consists of 279,566 (univariate) time series, each of length 3,750, representing recordings of wingbeats for six different species of mosquito [1, 2]. The recordings are single channel with a sampling rate of 6 kHz (i.e., the time series represent just over half a second of data).  As for the *FruitFlies* dataset, and using similar hardware, the recordings were made using an infrared sensor detecting the vibration of the wings of the mosquitoes.  The task is to identify the species of mosquito based on the recordings. This version of the dataset has been split into stratified random cross-validation folds.
 
 [1] Eleftherios Fanioudakis, Matthias Geismar, and Ilyas Potamitis. (2018). Mosquito wingbeat analysis and classification using deep learning. In *26<sup>th</sup> European Signal Processing Conference*, pages 2410–2414.