Update README.md

README.md

@@ -29,7 +29,7 @@ results:
          value: 81.87%
 ---
 
-# Wav2vec 2.0 XLS-R For Spontaneous Speech Recognition
+# Wav2vec 2.0 XLS-R For Spontaneous Speech Emotion Recognition
 
 This is the model that got first place in the SER track of the Automatic Speech Recognition for spontaneous and prepared speech & Speech Emotion Recognition in Portuguese (SE&R 2022) Workshop.
 
@@ -39,7 +39,7 @@ The following datasets were used in the training:
 
 - [EMOVO Corpus](https://aclanthology.org/L14-1478/): a database of emotional speech for the Italian language, built from the voices of up to 6 actors who played 14 sentences simulating 6 emotional states (disgust, fear, anger, joy, surprise, sadness) plus the neutral state.
 
-- [RAVDESS]((https://zenodo.org/record/1188976#.YO6yI-gzaUk)): a dataset that provides 1440 samples of recordings from actors performing on 8 different emotions in English, which are: angry, calm, disgust, fearful, happy, neutral, sad and surprised.
+- [RAVDESS](https://zenodo.org/record/1188976#.YO6yI-gzaUk): a dataset that provides 1440 samples of recordings from actors performing on 8 different emotions in English, which are: angry, calm, disgust, fearful, happy, neutral, sad and surprised.
 
 - [BAVED](https://github.com/40uf411/Basic-Arabic-Vocal-Emotions-Dataset): a collection of audio recordings of Arabic words spoken with varying degrees of emotion. The dataset contains seven words: like, unlike, this, file, good, neutral, and bad, which are spoken at three emotional levels: low emotion (tired or feeling down), neutral emotion (the way the speaker speaks daily), and high emotion (positive or negative emotions such as happiness, joy, sadness, anger).