Update README.md

README.md

@@ -28,7 +28,9 @@ This repository provides a pretrained ECAPA-TDNN model using SpeechBrain. The sy
 
 # Pipeline description
 
-This system is composed of an ECAPA-TDNN model. It is a combination of convolutional and residual blocks. The embeddings are extracted using attentive statistical pooling. The system is trained with Additive Margin Softmax Loss. It was trained using initial learning rate of 0.001 and batch size of 512 with cyclical learning rate policy (CLR) for 10 epochs on 4 A100 GPUs. We employ additive noises and reverberation from [MUSAN](http://www.openslr.org/17/) and [RIR](http://www.openslr.org/28/) datasets to enrich the supervised information. The pre-training progress takes approximately seven days for the ECAPA-TDNN model.
+This system is composed of an ECAPA-TDNN model. It is a combination of convolutional and residual blocks. The embeddings are extracted using attentive statistical pooling. The system is trained with Additive Margin Softmax Loss. 
+
+We use FBank (16kHz, 25ms frame length, 10ms hop length, 80 filter-bank channels) as the input features. It was trained using initial learning rate of 0.001 and batch size of 512 with cyclical learning rate policy (CLR) for 10 epochs on 4 A100 GPUs. We employ additive noises and reverberation from [MUSAN](http://www.openslr.org/17/) and [RIR](http://www.openslr.org/28/) datasets to enrich the supervised information. The pre-training progress takes approximately seven days for the ECAPA-TDNN model.
 
 # Performance