Initial dataset commit

.gitattributes

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+*.wav filter=lfs diff=lfs merge=lfs -text
+*.json filter=lfs diff=lfs merge=lfs -text

app.py

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+from pydub import AudioSegment
+
+def split_wav(file_name, number_of_parts):
+    audio = AudioSegment.from_wav(file_name)
+
+    length = len(audio) // number_of_parts
+
+    for i in range(number_of_parts):
+        start = length * i
+        end = start + length if i < number_of_parts - 1 else len(audio)
+        part = audio[start:end]
+        part.export(f"part_{i+1}.wav", format="wav")
+
+split_wav("craig.wav", 100)

craig.wav

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info.txt

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+Recording 8svf87tRmP
+
+Guild:		🌟AI Tonic🍹🌟 (1109943800132010065)
+Channel:	❤General (1109943800840851590)
+Requester:	Tonic (tonic_1#0) (994979735488692324)
+Start time:	2024-01-11T00:54:50.108Z
+
+Tracks:
+	Tonic (tonic_1#0) (994979735488692324)
+	n_raidenAI (nelectronica#0) (1112867759420878888)
+	John P (ehlive#0) (676956027727380489)

main.py

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+import requests
+import json
+
+def transcribe_audio(file_path, api_key, model='whisper-1', language=None, prompt=None, response_format='json', temperature=0):
+    url = "https://api.openai.com/v1/audio/transcriptions"
+
+    headers = {
+        "Authorization": f"Bearer {api_key}"
+    }
+
+    with open(file_path, 'rb') as f:
+        files = {
+            'file': (file_path, f, 'audio/wav')
+        }
+
+        data = {
+            'model': (None, model),
+            'language': (None, language),
+            'prompt': (None, prompt),
+            'response_format': (None, response_format),
+            'temperature': (None, str(temperature))
+        }
+
+        response = requests.post(url, headers=headers, files=files, data=data)
+        return response.json()
+
+def save_transcription(results, json_filename, text_filename):
+    # Save as JSON
+    with open(json_filename, 'w') as json_file:
+        json.dump(results, json_file, indent=4)
+
+    # Extract and save as text
+    transcripts = [result.get('choices')[0].get('text') if result.get('choices') else "" for result in results]
+    with open(text_filename, 'w') as text_file:
+        for transcript in transcripts:
+            text_file.write(transcript + "\n\n")
+
+# Replace 'your_api_key_here' with your actual OpenAI API key
+api_key = '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'
+
+# Generate list of audio files
+audio_files = [f'part_{i}.wav' for i in range(1, 101)]
+
+
+# Process each file and collect the results
+results = []
+for file_path in audio_files:
+    try:
+        result = transcribe_audio(file_path, api_key)
+        results.append(result)
+    except Exception as e:
+        print(f"Error processing {file_path}: {e}")
+
+# Save the results
+save_transcription(results, 'transcription.json', 'transcription.txt')
+
+print("Transcription saved to 'transcription.json' and 'transcription.txt'")

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