Update README.md

README.md

@@ -39,12 +39,6 @@ N blocks of convolutional neural networks with normalization and pooling on the
 frequency domain. Then, a bidirectional LSTM is connected to a final DNN to obtain
 the final acoustic representation that is given to the CTC and attention decoders.
 
-## Intended uses & limitations
-
-This model has been primarily developed to be run within SpeechBrain as a pretrained ASR model
-for the French language. Thanks to the flexibility of SpeechBrain, any of the 2 blocks
-detailed above can be extracted and connected to your custom pipeline as long as SpeechBrain is
-installed.
 
 ## Install SpeechBrain
 
@@ -70,6 +64,9 @@ asr_model.transcribe_file("speechbrain/asr-crdnn-commonvoice-fr/example-fr.wav")
 ### Inference on GPU
 To perform inference on the GPU, add  `run_opts={"device":"cuda"}`  when calling the `from_hparams` method.
 
+### Limitations
+The SpeechBrain team does not provide any warranty on the performance achieved by this model when used on other datasets.
+
 #### Referencing SpeechBrain
 
 ```
@@ -79,7 +76,7 @@ To perform inference on the GPU, add  `run_opts={"device":"cuda"}`  when calling
     year = {2021},
     publisher = {GitHub},
     journal = {GitHub repository},
-    howpublished = {\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\url{https://github.com/speechbrain/speechbrain}},
+    howpublished = {\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\url{https://github.com/speechbrain/speechbrain}},
   }
 ```