Update README.md

README.md

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-# Amharic Speech-to-Text Transcription
-
-## Group 10
-
-### Project Description
-This project focuses on developing a system for transcribing Amharic speech into text. The system aims to provide accurate and efficient transcription capabilities for the Amharic language, leveraging state-of-the-art technologies in speech recognition and natural language processing.
-
 ---
-
-### Group Members
-
-| **Name**                  | **ID**         |
-|---------------------------|----------------|
-| Yosef Ayele Eshetu        | UGR/2067/13    |
-| Yonas Engdu               | UGR/4575/13    |
-| Yosef Aweke Dinku         | UGR/5887/13    |
-| Yosef Muluneh Bane        | UGR/5715/13    |
-
+tags:
+- automatic-speech-recognition
+- asr
+- amharic
+- speech-to-text
+- wav2vec2
+- speechbrain
+- social-media
 ---
 
-### Technologies
-- Python for writing training scripts
-- Facebook's Wav2Vec2 as the base model
-- SpeechBrain for training
+# Amharic Speech-to-Text Transcription Model
 
----
+This model transcribes Amharic speech to text. It's built on **Facebook's Wav2Vec2** and trained using **SpeechBrain**.
 
-### Datasets Used for Fine-tuning
-- `facebook/2M-Belebele`
-- `fsicoli/common_voice_19_0`
+## Intended Use
 
----
+Its main purpose is to transcribe audio from **Instagram, YouTube, and TikTok video content** for further analysis (e.g., trend identification, content moderation).
 
+## Limitations
 
+Performance may vary with audio quality, background noise, and informal speech commonly found in social media.