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Merge pull request #282 from saenyakorn/master

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Add `progress_tracking_callback` argument to `get_speech_timestamps` function
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Dimitrii Voronin
2022-12-29 13:31:55 +02:00
committed by GitHub
parent d5a944b9f1 c69cb6c9c0
commit a480e85aec
1 changed files with 13 additions and 2 deletions
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15
utils_vad.py
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@@ -1,6 +1,6 @@
import torch import torch
import torchaudio import torchaudio
from typing import List from typing import Callable, List
import torch.nn.functional as F import torch.nn.functional as F
import warnings import warnings
@@ -168,7 +168,8 @@ def get_speech_timestamps(audio: torch.Tensor,
window_size_samples: int = 512, window_size_samples: int = 512,
speech_pad_ms: int = 30, speech_pad_ms: int = 30,
return_seconds: bool = False, return_seconds: bool = False,
visualize_probs: bool = False): visualize_probs: bool = False,
progress_tracking_callback: Callable[[float], None] = None):
""" """
This method is used for splitting long audios into speech chunks using silero VAD This method is used for splitting long audios into speech chunks using silero VAD
@@ -212,6 +213,9 @@ def get_speech_timestamps(audio: torch.Tensor,
visualize_probs: bool (default - False) visualize_probs: bool (default - False)
whether draw prob hist or not whether draw prob hist or not
progress_tracking_callback: Callable[[float], None] (default - None)
callback function taking progress in percents as an argument
Returns Returns
---------- ----------
speeches: list of dicts speeches: list of dicts
@@ -259,6 +263,13 @@ def get_speech_timestamps(audio: torch.Tensor,
chunk = torch.nn.functional.pad(chunk, (0, int(window_size_samples - len(chunk)))) chunk = torch.nn.functional.pad(chunk, (0, int(window_size_samples - len(chunk))))
speech_prob = model(chunk, sampling_rate).item() speech_prob = model(chunk, sampling_rate).item()
speech_probs.append(speech_prob) speech_probs.append(speech_prob)
# caculate progress and seng it to callback function
progress = current_start_sample + window_size_samples
if progress > audio_length_samples:
progress = audio_length_samples
progress_percent = (progress / audio_length_samples) * 100
if progress_tracking_callback:
progress_tracking_callback(progress_percent)
triggered = False triggered = False
speeches = [] speeches = []