Upload app.py

app.py

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+# -*- coding: utf-8 -*-
+"""GradioASRdemo.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1OgSEOxvR1jUIG-aE0dQHXpr9-ODs63Ll
+"""
+
+import gradio as gr
+import librosa
+from transformers import AutoFeatureExtractor, AutoModelForSeq2SeqLM, AutoTokenizer, pipeline
+
+model_name1 = "openai/whisper-tiny"
+feature_extractor = AutoFeatureExtractor.from_pretrained(model_name1)
+sampling_rate = feature_extractor.sampling_rate
+asr = pipeline("automatic-speech-recognition", model=model_name1)
+
+def speech_to_text(input_file):
+    transcribed_text = asr(input_file, chunk_length_s=30)  #, chunk_length_s=30
+    return transcribed_text["text"]
+
+
+#inputs=gr.Audio(source="upload", type="filepath", label="Upload your audio")
+inputs=gr.Audio(sources="upload", type="filepath", label="Upload Kannada audio file")
+# outputs=gr.Textbox()
+# examples = [["test1.wav"], ["test2.wav"]]
+description = "Demo for Kannada ASR model "
+
+gr.Interface(
+    speech_to_text,
+    inputs = inputs,
+    outputs = "text",
+    title="Kannada ASR model",
+).launch()
+# debug=True