Upload 3 files

README.md

@@ -0,0 +1,30 @@
+---
+license: cc-by-4.0
+---
+
+This corpus contains paired data of speech, articulatory movements and phonemes. There are 38 speakers in the corpus, each with 460 utterances.
+
+The raw audio files are in audios.zip. The ema data and preprocessed data is stored in processed.zip. The processed data can be loaded with pytorch and has the following keys - 
+
+<ul>
+<li>ema_raw : The raw ema data
+
+<li>ema_clipped : The ema data after trimming using being-end time stamps
+
+<li>ema_trimmed_and_normalised_with_6_articulators: The ema data after trimming using being-end time stamps, followed by articulatory specifc standardisation
+
+<li>mfcc: 13-dim MFCC computed on trimmed audio
+
+<li>phonemes: The phonemes uttered for the audio
+
+<li>durations: Duration values for each phoneme
+
+<li>begin_end: Begin end time stamps to trim the audio / raw ema
+</ul>
+To use this data for tasks such as acoustic to articulatory inversion (AAI), you can use ema_trimmed_and_normalised_with_6_articulators and mfcc as the data.
+
+___
+
+If you have used this dataset in your work, use the following refrence to cite the dataset - 
+
+```Bandekar, J., Udupa, S., Ghosh, P.K. (2024) Articulatory synthesis using representations learnt through phonetic label-aware contrastive loss. Proc. Interspeech 2024, 427-431, doi: 10.21437/Interspeech.2024-1756```

audios.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e07eaee117126ebc852593805b865798800a0438dd97cb423f50d1d2b1de2baf
+size 1656697958

processed.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ea1c3440af2b69cef0765b97e1e533ea72dae6029c49a175e1a93761c4236d04
+size 3086792402