Update README.md

README.md

@@ -96,13 +96,23 @@ Please notice that we encourage you to read our tutorials and learn more about
 
 ### Transcribing your own audio files (in English)
 
-TODO + streaming TODO
-
 ```python
 from speechbrain.inference.ASR import EncoderDecoderASR
-asr_model = EncoderDecoderASR.from_hparams(source="speechbrain/asr-conformer-transformerlm-librispeech", savedir="pretrained_models/asr-transformer-transformerlm-librispeech")
-asr_model.transcribe_file("speechbrain/asr-conformer-transformerlm-librispeech/example.wav")
+from speechbrain.utils.dynamic_chunk_training import DynChunkTrainConfig
+asr_model = EncoderDecoderASR.from_hparams(
+    source="speechbrain/asr-streaming-conformer-librispeech",
+    savedir="pretrained_models/asr-streaming-conformer-librispeech"
+)
+asr_model.transcribe_file(
+    "speechbrain/asr-streaming-conformer-librispeech/test-en.wav",
+    # select a chunk size of ~960ms with 4 chunks of left context
+    DynChunkTrainConfig(24, 4),
+    # disable torchaudio streaming to allow fetching from HuggingFace
+    # set this to True for your own files or streams to allow for streaming file decoding
+    use_torchaudio_streaming=False,
+)
 ```
+
 ### Inference on GPU
 To perform inference on the GPU, add  `run_opts={"device":"cuda"}`  when calling the `from_hparams` method.