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Datasets:
Tonic
/
Tonic-AI-Transcript-1-10-2024

Modalities:
Audio
Text
Formats:
soundfolder
Size:
< 1K
Libraries:
Datasets
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1
parquet-converter commited on
Commit
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1 Parent(s): 9902c89

Update parquet files

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Files changed (50) hide show
  1. .gitattributes +1 -0
  2. app.py +0 -14
  3. craig.wav +0 -3
  4. part_1.wav → default/train/0000.parquet +2 -2
  5. info.txt +0 -11
  6. main.py +0 -57
  7. part_10.wav +0 -3
  8. part_100.wav +0 -3
  9. part_11.wav +0 -3
  10. part_12.wav +0 -3
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.gitattributes CHANGED
@@ -1,2 +1,3 @@
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  *.wav filter=lfs diff=lfs merge=lfs -text
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  *.json filter=lfs diff=lfs merge=lfs -text
 
 
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  *.wav filter=lfs diff=lfs merge=lfs -text
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  *.json filter=lfs diff=lfs merge=lfs -text
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+ default/train/0000.parquet filter=lfs diff=lfs merge=lfs -text
app.py DELETED
@@ -1,14 +0,0 @@
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- from pydub import AudioSegment
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-
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- def split_wav(file_name, number_of_parts):
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- audio = AudioSegment.from_wav(file_name)
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- length = len(audio) // number_of_parts
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- start = length * i
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- end = start + length if i < number_of_parts - 1 else len(audio)
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- part = audio[start:end]
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- part.export(f"part_{i+1}.wav", format="wav")
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-
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- size 3922796
 
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info.txt DELETED
@@ -1,11 +0,0 @@
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- Recording 8svf87tRmP
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-
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- Guild: 🌟AI Tonic🍹🌟 (1109943800132010065)
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- Channel: ❤General (1109943800840851590)
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- Requester: Tonic (tonic_1#0) (994979735488692324)
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- Start time: 2024-01-11T00:54:50.108Z
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-
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- Tracks:
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- Tonic (tonic_1#0) (994979735488692324)
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- n_raidenAI (nelectronica#0) (1112867759420878888)
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- John P (ehlive#0) (676956027727380489)
 
 
 
 
 
 
 
 
 
 
 
 
main.py DELETED
@@ -1,57 +0,0 @@
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- import requests
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- import json
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-
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- def transcribe_audio(file_path, api_key, model='whisper-1', language=None, prompt=None, response_format='json', temperature=0):
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- url = "https://api.openai.com/v1/audio/transcriptions"
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-
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- headers = {
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- "Authorization": f"Bearer {api_key}"
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- }
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-
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- with open(file_path, 'rb') as f:
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- files = {
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- 'file': (file_path, f, 'audio/wav')
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- }
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-
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- data = {
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- 'model': (None, model),
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- 'language': (None, language),
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- 'prompt': (None, prompt),
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- 'response_format': (None, response_format),
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- 'temperature': (None, str(temperature))
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- }
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-
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- response = requests.post(url, headers=headers, files=files, data=data)
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- return response.json()
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-
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- def save_transcription(results, json_filename, text_filename):
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- # Save as JSON
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- with open(json_filename, 'w') as json_file:
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- json.dump(results, json_file, indent=4)
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-
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- # Extract and save as text
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- transcripts = [result.get('choices')[0].get('text') if result.get('choices') else "" for result in results]
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- with open(text_filename, 'w') as text_file:
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- for transcript in transcripts:
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- text_file.write(transcript + "\n\n")
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-
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- # Replace 'your_api_key_here' with your actual OpenAI API key
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- api_key = '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'
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-
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- # Generate list of audio files
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- audio_files = [f'part_{i}.wav' for i in range(1, 101)]
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-
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-
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- # Process each file and collect the results
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- results = []
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- for file_path in audio_files:
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- try:
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- result = transcribe_audio(file_path, api_key)
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- results.append(result)
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- except Exception as e:
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- print(f"Error processing {file_path}: {e}")
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-
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- # Save the results
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- save_transcription(results, 'transcription.json', 'transcription.txt')
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-
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- print("Transcription saved to 'transcription.json' and 'transcription.txt'")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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