Merge pull request #20 from hendriks73/patch-1

Update README.md

Author: jim-schwoebel

README.md

@@ -15,7 +15,7 @@ There are two main types of audio datasets: speech datasets and audio event/musi
 * [Awesome_Diarization](https://github.com/jim-schwoebel/awesome-diarization) - A curated list of awesome Speaker Diarization papers, libraries, datasets, and other resources. 
 * [BAVED](https://www.kaggle.com/a13x10/basic-arabic-vocal-emotions-dataset) - 1935 recording by 61 speakers (45 male and 16 female).
 * [CaFE](https://www.gel.usherbrooke.ca/audio/cafe.htm) - 6 different sentences by 12 speakers (6 fmelaes + 6 males).
-* [Common Voice](https://voice.mozilla.org/) - Common Voice is Mozilla's initiative to help teach machines how real people speak. 12GB in size; spoken text based on text from a number of public domain sources like user-submitted blog posts, old books, movies, and other public speech corpora.
+* [Common Voice](https://commonvoice.mozilla.org/en/datasets) - Common Voice is Mozilla's initiative to help teach machines how real people speak. 12GB in size; spoken text based on text from a number of public domain sources like user-submitted blog posts, old books, movies, and other public speech corpora.
 * [CHIME](https://archive.org/details/chime-home) - This is a noisy speech recognition challenge dataset (~4GB in size). The dataset contains real simulated and clean voice recordings. Real being actual recordings of 4 speakers in nearly 9000 recordings over 4 noisy locations, simulated is generated by combining multiple environments over speech utterances and clean being non-noisy recordings. 
 * [Coswara](https://github.com/iiscleap/Coswara-Data) - A database that contains respiratory sounds, namely, cough, breath, and speech of healthy and COVID-19 positive individuals.
 * [CMU-MOSEI](https://www.amir-zadeh.com/datasets) - 65 hours of annotated video from more than 1000 speakers and 250 topics; 6 Emotion (happiness, sadness, anger,fear, disgust, surprise) + Likert scale.