update

README.md

@@ -4,11 +4,14 @@ language:
 - bn
 base_model:
 - openai/whisper-small
+
 pipeline_tag: automatic-speech-recognition
 
 ---
-```py
+BengaliRegionalASR trained on bengali regional dialact dataset. 
 
+# Try the model
+```py
 import os
 import librosa
 import torch, torchaudio
@@ -22,7 +25,7 @@ processor = WhisperProcessor.from_pretrained(model_path_)
 model = WhisperForConditionalGeneration.from_pretrained(model_path_).to(device)
 model.config.forced_decoder_ids = processor.get_decoder_prompt_ids(language="bengali", task="transcribe")
 
-mp3_path = "/kaggle/input/barishal-data/valid_barishal (104).wav"
+mp3_path = "https://huggingface.co/sha1779/BengaliRegionalASR/resolve/main/Mp3/common_voice_bn_31617644.mp3"
 speech_array, sampling_rate = librosa.load(mp3_path, sr=16000)
 
 speech_array = librosa.resample(np.asarray(speech_array), orig_sr=sampling_rate, target_sr=16000)
@@ -34,5 +37,10 @@ transcription = processor.decode(predicted_ids, skip_special_tokens=True)
 
 print(transcription)
 
+```
+
+# Evaluation
+Word Error Rate 0.65 %
+
+
 
-```