Update README.md

README.md

@@ -74,6 +74,7 @@ language:
 - quy
 - ro
 - ru
+- rw
 - sah
 - sat
 - sc
@@ -82,6 +83,7 @@ language:
 - sl
 - sq
 - sr
+- sw
 - ta
 - th
 - ti
@@ -114,9 +116,14 @@ tags:
 
 <!-- Provide a quick summary of the dataset. -->
 
-This dataset is an unofficial converted version of the Mozilla Common Voice Corpus 15. It currently contains the following languages: Arabic, French, Georgian, German, Hebrew, Italian, Portuguese, and Spanish, among others. Additional languages are being converted and will be uploaded in the next few days.
+This dataset is an unofficial version of the Mozilla Common Voice Corpus 15. It was downloaded and converted from the project's website https://commonvoice.mozilla.org/.
 
 
+## Languages
+```
+Abkhaz, Albanian, Amharic, Arabic, Armenian, Assamese, Asturian, Azerbaijani, Basaa, Bashkir, Basque, Belarusian, Bengali, Breton, Bulgarian, Cantonese, Catalan, Central Kurdish, Chinese (China), Chinese (Hong Kong), Chinese (Taiwan), Chuvash, Czech, Danish, Dhivehi, Dioula, Dutch, English, Erzya, Esperanto, Estonian, Finnish, French, Frisian, Galician, Georgian, German, Greek, Guarani, Hakha Chin, Hausa, Hill Mari, Hindi, Hungarian, Icelandic, Igbo, Indonesian, Interlingua, Irish, Italian, Japanese, Kabyle, Kazakh, Kinyarwanda, Korean, Kurmanji Kurdish, Kyrgyz, Lao, Latvian, Lithuanian, Luganda, Macedonian, Malayalam, Maltese, Marathi, Meadow Mari, Moksha, Mongolian, Nepali, Norwegian Nynorsk, Occitan, Odia, Pashto, Persian, Polish, Portuguese, Punjabi, Quechua Chanka, Romanian, Romansh Sursilvan, Romansh Vallader, Russian, Sakha, Santali (Ol Chiki), Saraiki, Sardinian, Serbian, Slovak, Slovenian, Sorbian, Upper, Spanish, Swahili, Swedish, Taiwanese (Minnan), Tamazight, Tamil, Tatar, Thai, Tigre, Tigrinya, Toki Pona, Turkish, Turkmen, Twi, Ukrainian, Urdu, Uyghur, Uzbek, Vietnamese, Votic, Welsh, Yoruba
+```
+
 ## How to use
 The datasets library allows you to load and pre-process your dataset in pure Python, at scale. The dataset can be downloaded and prepared in one call to your local drive by using the load_dataset function.