Update README.md

README.md

@@ -38,9 +38,9 @@ from clearvoice import ClearVoice
 
 myClearVoice = ClearVoice(task='speech_super_resolution', model_names=['MossFormer2_SR_48K'])
 
-output_wav = myClearVoice(input_path='samples/input.wav', online_write=False)
+output_wav = myClearVoice(input_path='samples/input_sr.wav', online_write=False)
 
-myClearVoice.write(output_wav, output_path='samples/output_MossFormer2_SR_48K.wav')
+myClearVoice.write(output_wav, output_path='samples/output_MossFormer2_SR_48K_input_sr.wav')
 ```
 
 Sample example 2: use speech enhancement model `MossFormer2_SE_48K` to process all input wave files in `samples/path_to_input_wavs/` and save all output files to `samples/path_to_output_wavs`
@@ -50,7 +50,7 @@ from clearvoice import ClearVoice
 
 myClearVoice = ClearVoice(task='speech_super_resolution', model_names=['MossFormer2_SR_48K'])
 
-myClearVoice(input_path='samples/path_to_input_wavs', online_write=True, output_path='samples/path_to_output_wavs')
+myClearVoice(input_path='samples/path_to_input_wavs_sr', online_write=True, output_path='samples/path_to_output_wavs')
 ```
 
 Sample example 3: use speech enhancement model `MossFormer2_SE_48K` to process wave files listed in `samples/audio_samples.scp' file, and save all output files to 'samples/path_to_output_wavs_scp/'
@@ -60,7 +60,7 @@ from clearvoice import ClearVoice
 
 myClearVoice = ClearVoice(task='speech_super_resolution', model_names=['MossFormer2_SR_48K'])
 
-myClearVoice(input_path='samples/scp/audio_samples.scp', online_write=True, output_path='samples/path_to_output_wavs_scp')
+myClearVoice(input_path='samples/scp/audio_samples_sr.scp', online_write=True, output_path='samples/path_to_output_wavs_scp')
 ```
 
 Model Limitations: The current speech super-resolution model is trained on a clean speech dataset and is designed to work with clean speech inputs. For speech super-resolution on noisy speech audio,