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voice-matcher-api
Running on T4

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arnabg95 commited on
Commit
2c92e3b
•
1 Parent(s): 0066b69

model changed

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Files changed (6) hide show
  1. app/__pycache__/main.cpython-310.pyc +0 -0
  2. app/__pycache__/passing.cpython-310.pyc +0 -0
  3. app/__pycache__/transcriber.cpython-310.pyc +0 -0
  4. app/passing.py +1 -1
  5. app/routers/V1/voice/__pycache__/voice_router.cpython-310.pyc +0 -0
  6. app/transcriber.py +1 -1
app/__pycache__/main.cpython-310.pyc CHANGED
Binary files a/app/__pycache__/main.cpython-310.pyc and b/app/__pycache__/main.cpython-310.pyc differ
 
app/__pycache__/passing.cpython-310.pyc CHANGED
Binary files a/app/__pycache__/passing.cpython-310.pyc and b/app/__pycache__/passing.cpython-310.pyc differ
 
app/__pycache__/transcriber.cpython-310.pyc CHANGED
Binary files a/app/__pycache__/transcriber.cpython-310.pyc and b/app/__pycache__/transcriber.cpython-310.pyc differ
 
app/passing.py CHANGED
@@ -5,7 +5,7 @@ def normalize_euclidean(euclidean, max_value):
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  """
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  return max(0, 100 - (euclidean / max_value) * 100)
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- def calculate_passing(sequence, phonetic, cosine, euclidean, passing_threshold=70, euclidean_max=200):
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  # Normalize sequence and phonetic to 0-100 scale
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  sequence_normalized = sequence * 100
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  phonetic_normalized = phonetic * 100
 
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  """
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  return max(0, 100 - (euclidean / max_value) * 100)
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+ def calculate_passing(sequence, phonetic, cosine, euclidean, passing_threshold=60, euclidean_max=200):
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  # Normalize sequence and phonetic to 0-100 scale
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  sequence_normalized = sequence * 100
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  phonetic_normalized = phonetic * 100
app/routers/V1/voice/__pycache__/voice_router.cpython-310.pyc CHANGED
Binary files a/app/routers/V1/voice/__pycache__/voice_router.cpython-310.pyc and b/app/routers/V1/voice/__pycache__/voice_router.cpython-310.pyc differ
 
app/transcriber.py CHANGED
@@ -6,7 +6,7 @@ from datasets import load_dataset
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  device = "cuda:0" if torch.cuda.is_available() else "cpu"
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  torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
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- model_id = "openai/whisper-large-v3"
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  model = AutoModelForSpeechSeq2Seq.from_pretrained(
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  model_id, torch_dtype=torch_dtype, low_cpu_mem_usage=True, use_safetensors=True
 
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  device = "cuda:0" if torch.cuda.is_available() else "cpu"
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  torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
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+ model_id = "MothersTongue/mother_tongue_model"
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  model = AutoModelForSpeechSeq2Seq.from_pretrained(
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  model_id, torch_dtype=torch_dtype, low_cpu_mem_usage=True, use_safetensors=True