Update README.md

README.md

@@ -22,6 +22,13 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc0-1.0
+task_categories:
+- automatic-speech-recognition
+- text-to-speech
+language:
+- cv
+pretty_name: Chuvash Voice
 ---
 
 ## How to use
@@ -34,7 +41,7 @@ from datasets import load_dataset, DatasetDict, concatenate_datasets, Audio
 comm_voice = DatasetDict()
 comm_voice["train"] = load_dataset("mozilla-foundation/common_voice_17_0", "cv", split="train+validation", use_auth_token=True)
 comm_voice["test"] = load_dataset("mozilla-foundation/common_voice_17_0", "cv", split="test", use_auth_token=True)
-comm_voice = comm_voice.remove_columns(["accent", "age", "client_id", "down_votes", "gender", "segment", "up_votes", "variant"])
+comm_voice = comm_voice.remove_columns(["accent", "age", "down_votes", "gender", "segment", "up_votes", "variant"])
 comm_voice = comm_voice.cast_column("audio", Audio(sampling_rate=16000))
 
 print(comm_voice)
@@ -52,3 +59,7 @@ common_voice = DatasetDict({"train": concatenate_datasets([comm_voice["train"],
 
 print(common_voice)
 ```
+
+## Text to Speech
+
+Most of the corpus is a unique voice (client_id='177'). Therefore, the corpus can also be used for synthesis tasks.