Returning Speech Probabilities

[qiisziilbash]

Is there any function/way to get the speech probs directly?

[snakers4]

silero-vad/src/silero_vad/utils_vad.py

Lines 291 to 297 in 93b9782

	speech_probs = []
	for current_start_sample in range(0, audio_length_samples, window_size_samples):
	chunk = audio[current_start_sample: current_start_sample + window_size_samples]
	if len(chunk) < window_size_samples:
	chunk = torch.nn.functional.pad(chunk, (0, int(window_size_samples - len(chunk))))
	speech_prob = model(chunk, sampling_rate).item()
	speech_probs.append(speech_prob)

[snakers4]

Or

silero-vad/src/silero_vad/utils_vad.py

Lines 56 to 91 in 93b9782

	def __call__(self, x, sr: int):
	x, sr = self._validate_input(x, sr)
	num_samples = 512 if sr == 16000 else 256
	if x.shape[-1] != num_samples:
	raise ValueError(f"Provided number of samples is {x.shape[-1]} (Supported values: 256 for 8000 sample rate, 512 for 16000)")
	batch_size = x.shape[0]
	context_size = 64 if sr == 16000 else 32
	if not self._last_batch_size:
	self.reset_states(batch_size)
	if (self._last_sr) and (self._last_sr != sr):
	self.reset_states(batch_size)
	if (self._last_batch_size) and (self._last_batch_size != batch_size):
	self.reset_states(batch_size)
	if not len(self._context):
	self._context = torch.zeros(batch_size, context_size)
	x = torch.cat([self._context, x], dim=1)
	if sr in [8000, 16000]:
	ort_inputs = {'input': x.numpy(), 'state': self._state.numpy(), 'sr': np.array(sr, dtype='int64')}
	ort_outs = self.session.run(None, ort_inputs)
	out, state = ort_outs
	self._state = torch.from_numpy(state)
	else:
	raise ValueError()
	self._context = x[..., -context_size:]
	self._last_sr = sr
	self._last_batch_size = batch_size
	out = torch.from_numpy(out)
	return out