module for finding context similarity between audio files

audio_comp.py

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+import deepspeech
+import time
+import wave
+import numpy as np 
+import pyaudio
+from audio_gen import user_audio 
+import glob
+
+import soundfile as sf
+import torch
+from transformers import Wav2Vec2ForCTC, Wav2Vec2Tokenizer
+
+import deep_speech 
+import wav2vec
+
+from text_gen import text_gen
+
+import tensorflow as tf 
+import tensorflow_hub as hub
+
+# Module for calculating similarity between the audios 
+
+module_url = "https://tfhub.dev/google/universal-sentence-encoder/4"
+embed_model = hub.load(module_url)
+
+def cosine(u, v):
+	return np.dot(u, v) / (np.linalg.norm(u) * np.linalg.norm(v))
+
+# Function to find similarity between 2 audios from the file 
+# path to the files 
+def similarity(audio1, audio2, model='deepspeech'):
+	gen = text_gen(model=model)
+
+	text1 = gen.text_from_file(audio1)
+	text2 = gen.text_from_file(audio2)
+
+	query = embed_model([text1])[0]
+	target =embed_model([text2])[0]
+
+	sim = cosine(query, target)
+
+	return sim 
+
+
+