From 62592d7cef2b2fc16ecd267ac11c3e7695e08997 Mon Sep 17 00:00:00 2001
From: Jonatas Grosman <jonatasgrosman@gmail.com>
Date: Tue, 22 Feb 2022 21:45:06 +0000
Subject: [PATCH] Update README.md

---
 README.md | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/README.md b/README.md
index 98bdd25..6a19553 100644
--- a/README.md
+++ b/README.md
@@ -22,7 +22,7 @@ model-index:
       name: Automatic Speech Recognition 
       type: automatic-speech-recognition
     dataset:
-      name: Common Voice pt
+      name: Common Voice en
       type: common_voice
       args: en
     metrics:
@@ -73,15 +73,15 @@ The script used for training can be found here: https://github.com/jonatasgrosma
 
 The model can be used directly (without a language model) as follows...
 
-Using the [ASRecognition](https://github.com/jonatasgrosman/asrecognition) library:
+Using the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) library:
 
 ```python
-from asrecognition import ASREngine
-
-asr = ASREngine("en", model_path="jonatasgrosman/wav2vec2-large-xlsr-53-english")
+from huggingsound import SpeechRecognitionModel
 
+model = SpeechRecognitionModel("jonatasgrosman/wav2vec2-large-xlsr-53-english")
 audio_paths = ["/path/to/file.mp3", "/path/to/another_file.wav"]
-transcriptions = asr.transcribe(audio_paths)
+
+transcriptions = model.transcribe(audio_paths)
 ```
 
 Writing your own inference script: