Update README.md

README.md

@@ -26,11 +26,11 @@ The model uses an ASR model trained on LibriSpeech ([`speechbrain/asr-crdnn-rnnl
 
 You can try the model on the `example_fsc.wav` file included here as follows:
 ```
->>> from speechbrain.pretrained import EndToEndSLU
->>> slu = EndToEndSLU.from_hparams("/network/tmp1/ravanelm/slu-direct-fluent-speech-commands-librispeech-asr")
->>> # Text: "Please, turn on the light of the bedroom"
->>> slu.decode_file("/network/tmp1/ravanelm/slu-direct-fluent-speech-commands-librispeech-asr/example_fsc.wav")
-'{"action:" "activate"| "object": "lights"| "location": "bedroom"}'
+from speechbrain.pretrained import EndToEndSLU
+slu = EndToEndSLU.from_hparams("/network/tmp1/ravanelm/slu-direct-fluent-speech-commands-librispeech-asr")
+# Text: "Please, turn on the light of the bedroom"
+slu.decode_file("/network/tmp1/ravanelm/slu-direct-fluent-speech-commands-librispeech-asr/example_fsc.wav")
+>>> '{"action:" "activate"| "object": "lights"| "location": "bedroom"}'
 ```
 ### Inference on GPU
 To perform inference on the GPU, add  `run_opts={"device":"cuda"}`  when calling the `from_hparams` method.
@@ -69,7 +69,7 @@ title = {SpeechBrain},
 year = {2021},
 publisher = {GitHub},
 journal = {GitHub repository},
-howpublished = {\url{https://github.com/speechbrain/speechbrain}},
+howpublished = {\\url{https://github.com/speechbrain/speechbrain}},
 }
 ```