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https://github.com/snakers4/silero-vad.git
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@@ -13,11 +13,11 @@ class OnnxWrapper():
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import numpy as np
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import numpy as np
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global np
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global np
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import onnxruntime
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import onnxruntime
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opts = onnxruntime.SessionOptions()
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opts = onnxruntime.SessionOptions()
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opts.inter_op_num_threads = 1
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opts.inter_op_num_threads = 1
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opts.intra_op_num_threads = 1
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opts.intra_op_num_threads = 1
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if force_onnx_cpu and 'CPUExecutionProvider' in onnxruntime.get_available_providers():
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if force_onnx_cpu and 'CPUExecutionProvider' in onnxruntime.get_available_providers():
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self.session = onnxruntime.InferenceSession(path, providers=['CPUExecutionProvider'], sess_options=opts)
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self.session = onnxruntime.InferenceSession(path, providers=['CPUExecutionProvider'], sess_options=opts)
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else:
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else:
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@@ -34,7 +34,7 @@ class OnnxWrapper():
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if sr != 16000 and (sr % 16000 == 0):
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if sr != 16000 and (sr % 16000 == 0):
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step = sr // 16000
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step = sr // 16000
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x = x[::step]
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x = x[:, ::step]
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sr = 16000
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sr = 16000
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if sr not in self.sample_rates:
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if sr not in self.sample_rates:
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@@ -291,7 +291,7 @@ def get_speech_timestamps(audio: torch.Tensor,
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triggered = True
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triggered = True
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current_speech['start'] = window_size_samples * i
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current_speech['start'] = window_size_samples * i
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continue
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continue
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if triggered and (window_size_samples * i) - current_speech['start'] > max_speech_samples:
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if triggered and (window_size_samples * i) - current_speech['start'] > max_speech_samples:
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if prev_end:
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if prev_end:
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current_speech['end'] = prev_end
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current_speech['end'] = prev_end
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@@ -309,7 +309,6 @@ def get_speech_timestamps(audio: torch.Tensor,
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prev_end = next_start = temp_end = 0
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prev_end = next_start = temp_end = 0
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triggered = False
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triggered = False
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continue
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continue
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if (speech_prob < neg_threshold) and triggered:
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if (speech_prob < neg_threshold) and triggered:
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if not temp_end:
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if not temp_end:
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