Spaces:
Runtime error
Runtime error
File size: 6,474 Bytes
890de26 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 |
# -*- coding:utf-8 -*-
# @FileName :fsmnVadInfer.py
# @Time :2023/8/9 09:30
# @Author :lovemefan
# @Email :[email protected]
# -*- coding:utf-8 -*-
# @FileName :fsmnvad.py
# @Time :2023/3/31 16:06
# @Author :lovemefan
# @Email :[email protected]
__author__ = "lovemefan"
__copyright__ = "Copyright (C) 2016 lovemefan"
__license__ = "MIT"
__version__ = "v0.0.1"
import os.path
from pathlib import Path
from typing import Tuple, Union
import numpy as np
from paraformer.runtime.python.model.vad.fsmnvad import E2EVadModel
from paraformer.runtime.python.utils.asrOrtInferRuntimeSession import read_yaml
from paraformer.runtime.python.utils.audioHelper import AudioReader
from paraformer.runtime.python.utils.logger import logger
from paraformer.runtime.python.utils.preprocess import (WavFrontend,
WavFrontendOnline)
root_dir = Path(
os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
)
class FSMNVad(object):
def __init__(self, config_path=root_dir / "onnx/vad/config.yaml"):
self.config = read_yaml(config_path)
self.frontend = WavFrontend(
cmvn_file=root_dir / "onnx/vad/am.mvn",
**self.config["WavFrontend"]["frontend_conf"],
)
self.config["FSMN"]["model_path"] = root_dir / "onnx/vad/fsmnvad-offline.onnx"
self.vad = E2EVadModel(
self.config["FSMN"], self.config["vadPostArgs"], root_dir
)
def set_parameters(self, mode):
pass
def extract_feature(self, waveform):
fbank, _ = self.frontend.fbank(waveform)
feats, feats_len = self.frontend.lfr_cmvn(fbank)
return feats.astype(np.float32), feats_len
def is_speech(self, buf, sample_rate=16000):
assert sample_rate == 16000, "only support 16k sample rate"
def segments_offline(self, waveform_path: Union[str, Path, np.ndarray]):
"""get sements of audio"""
if isinstance(waveform_path, np.ndarray):
waveform = waveform_path
else:
if not os.path.exists(waveform_path):
raise FileExistsError(f"{waveform_path} is not exist.")
if os.path.isfile(waveform_path):
logger.info(f"load audio {waveform_path}")
waveform, _sample_rate = AudioReader.read_wav_file(waveform_path)
else:
raise FileNotFoundError(str(Path))
assert (
_sample_rate == 16000
), f"only support 16k sample rate, current sample rate is {_sample_rate}"
feats, feats_len = self.extract_feature(waveform)
waveform = waveform[None, ...]
segments_part, in_cache = self.vad.infer_offline(
feats[None, ...], waveform, is_final=True
)
if segments_part == []:
return 0
return segments_part[0]
class FSMNVadOnline:
def __init__(self, config_path=None):
project_dir = os.path.dirname(os.path.dirname(os.path.dirname(__file__)))
config_path = config_path or os.path.join(
project_dir, "onnx", "vad", "config.yaml"
)
self.config = read_yaml(config_path)
self.frontend = WavFrontendOnline(
cmvn_file=root_dir / "onnx/vad/am.mvn",
**self.config["WavFrontend"]["frontend_conf"],
)
self.config["FSMN"]["model_path"] = root_dir / "onnx/vad/fsmnvad-online.onnx"
self.vad = E2EVadModel(
self.config["FSMN"], self.config["vadPostArgs"], root_dir
)
self.in_cache = None
def extract_feature(
self, waveforms: np.ndarray, is_final: bool = False
) -> Tuple[np.ndarray, np.ndarray]:
waveforms_lens = np.zeros(waveforms.shape[0]).astype(np.int32)
for idx, waveform in enumerate(waveforms):
waveforms_lens[idx] = waveform.shape[-1]
feats, feats_len = self.frontend.extract_fbank(
waveforms, waveforms_lens, is_final
)
return feats.astype(np.float32), feats_len.astype(np.int32)
def is_speech(self, buf, sample_rate=16000):
assert sample_rate == 16000, "only support 16k sample rate"
def prepare_cache(self, in_cache: list):
if len(in_cache) > 0:
return in_cache
fsmn_layers = self.config["FSMN"]["encoder_conf"]["fsmn_layers"]
proj_dim = self.config["FSMN"]["encoder_conf"]["proj_dim"]
lorder = self.config["FSMN"]["encoder_conf"]["lorder"]
for i in range(fsmn_layers):
cache = np.zeros((1, proj_dim, lorder - 1, 1)).astype(np.float32)
in_cache.append(cache)
return in_cache
def segments_online(
self, waveform: Union[str, np.ndarray], sample_rate=16000, is_final=False
):
"""
get sements of audio
"""
if self.in_cache is None:
self.in_cache = []
if isinstance(waveform, str):
waveform = AudioReader.read_pcm_byte(waveform)
assert (
sample_rate == 16000
), f"only support 16k sample rate, current sample rate is {sample_rate}"
if waveform.ndim == 1:
waveform = waveform[None, ...]
feats, feats_len = self.extract_feature(waveform)
waveform = self.frontend.get_waveforms()
segments_part, self.in_cache = self.vad.infer_online(
feats, waveform, self.prepare_cache(self.in_cache), is_final=is_final
)
return segments_part
def segments_online_with_speaker_verification(
self, waveform: Union[str, np.ndarray], sample_rate=16000, is_final=False
):
"""
get sements of audio with vad and speaker verificaton
"""
if self.in_cache is None:
self.in_cache = []
if isinstance(waveform, str):
waveform = AudioReader.read_pcm_byte(waveform)
assert (
sample_rate == 16000
), f"only support 16k sample rate, current sample rate is {sample_rate}"
if waveform.ndim == 1:
waveform = waveform[None, ...]
feats, feats_len = self.extract_feature(waveform)
waveform = self.frontend.get_waveforms()
segments_part, self.in_cache = self.vad.infer_online(
feats, waveform, self.prepare_cache(self.in_cache), is_final=is_final
)
# segment again with speaker verification model
return segments_part
|