deepgeek/silero-vad
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del numpy dependency

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adamnsandle
2020-12-15 13:02:17 +00:00
parent 40dd30780f
commit f9f8919623
2 changed files with 7 additions and 8 deletions
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2
hubconf.py
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@@ -1,4 +1,4 @@
dependencies = ['torch', 'torchaudio', 'numpy'] dependencies = ['torch', 'torchaudio']
import torch import torch
from utils import (init_jit_model, from utils import (init_jit_model,
get_speech_ts, get_speech_ts,

13
utils.py
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@@ -1,6 +1,5 @@
import torch import torch
import torchaudio import torchaudio
import numpy as np
from typing import List from typing import List
from itertools import repeat from itertools import repeat
from collections import deque from collections import deque
@@ -90,10 +89,10 @@ def get_speech_ts(wav: torch.Tensor,
speech_probs = outs[:, 1] # this is very misleading speech_probs = outs[:, 1] # this is very misleading
for i, predict in enumerate(speech_probs): # add name for i, predict in enumerate(speech_probs): # add name
buffer.append(predict) buffer.append(predict)
if (np.mean(buffer) >= trig_sum) and not triggered: if ((sum(buffer) / len(buffer))>= trig_sum) and not triggered:
triggered = True triggered = True
current_speech['start'] = step * max(0, i-num_steps) current_speech['start'] = step * max(0, i-num_steps)
if (np.mean(buffer) < neg_trig_sum) and triggered: if ((sum(buffer) / len(buffer)) < neg_trig_sum) and triggered:
current_speech['end'] = step * i current_speech['end'] = step * i
if (current_speech['end'] - current_speech['start']) > 10000: if (current_speech['end'] - current_speech['start']) > 10000:
speeches.append(current_speech) speeches.append(current_speech)
@@ -152,10 +151,10 @@ class VADiterator:
speech_probs = model_out[:, 1] # this is very misleading speech_probs = model_out[:, 1] # this is very misleading
for i, predict in enumerate(speech_probs): for i, predict in enumerate(speech_probs):
self.buffer.append(predict) self.buffer.append(predict)
if (np.mean(self.buffer) >= self.trig_sum) and not self.triggered: if ((sum(self.buffer) / len(self.buffer)) >= self.trig_sum) and not self.triggered:
self.triggered = True self.triggered = True
current_speech[self.num_frames - (self.num_steps-i) * self.step] = 'start' current_speech[self.num_frames - (self.num_steps-i) * self.step] = 'start'
if (np.mean(self.buffer) < self.neg_trig_sum) and self.triggered: if ((sum(self.buffer) / len(self.buffer)) < self.neg_trig_sum) and self.triggered:
current_speech[self.num_frames - (self.num_steps-i) * self.step] = 'end' current_speech[self.num_frames - (self.num_steps-i) * self.step] = 'end'
self.triggered = False self.triggered = False
if self.triggered and self.last: if self.triggered and self.last:
@@ -171,7 +170,7 @@ def state_generator(model,
trig_sum: float = 0.26, trig_sum: float = 0.26,
neg_trig_sum: float = 0.02, neg_trig_sum: float = 0.02,
num_steps: int = 8, num_steps: int = 8,
audios_in_stream: int = 5, audios_in_stream: int = 2,
run_function=validate): run_function=validate):
VADiters = [VADiterator(trig_sum, neg_trig_sum, num_steps) for i in range(audios_in_stream)] VADiters = [VADiterator(trig_sum, neg_trig_sum, num_steps) for i in range(audios_in_stream)]
for i, current_pieces in enumerate(stream_imitator(audios, audios_in_stream)): for i, current_pieces in enumerate(stream_imitator(audios, audios_in_stream)):
@@ -179,7 +178,7 @@ def state_generator(model,
batch = torch.cat(for_batch) batch = torch.cat(for_batch)
outs = run_function(model, batch) outs = run_function(model, batch)
vad_outs = np.split(outs[-2].numpy(), audios_in_stream) vad_outs = torch.split(outs[-2], num_steps)
states = [] states = []
for x, y in zip(VADiters, vad_outs): for x, y in zip(VADiters, vad_outs):