Update README.md

README.md

@@ -54,7 +54,8 @@ English.
 The TIE_shorts version (~ 70 hours) was created to facilitate efficient training and usage in speech processing tasks by providing shorter audio samples. In TIE_shorts, 
 consecutive audio snippets from the original dataset were merged based on timestamps, with a condition that the final merged audio should not exceed 30 seconds in duration.
 This process results in 25–30 second audio clips, each accompanied by a corresponding ground-truth transcript. This approach retains the linguistic diversity of the original 
-dataset while significantly reducing the size and complexity, making TIE_shorts ideal for Automatic Speech Recognition (ASR) and other speech-to-text applications.
+dataset while significantly reducing the size and complexity, making TIE_shorts ideal for Automatic Speech Recognition (ASR) and other speech-to-text applications. 
+As the dataset consisting of approximately 9.8K files spoken by 331 speakers from diverse demographics across the Indian population, this data is also well-suited for speaker identification and text-to-speech (TTS) training applications.
 
 ### Example usage