import collections
import numpy as np
from audiomate.utils import units
from . import label
[docs]class Utterance(object):
"""
An utterance defines a sample of audio. It is part of a file or can span over the whole file.
Args:
idx (str): A unique identifier for the utterance within a dataset.
file (File): The file this utterance is belonging to.
issuer (Issuer): The issuer this utterance was created from.
start (float): The start of the utterance within the audio file in seconds. (default 0)
end (float): The end of the utterance within the audio file in seconds. -1 indicates that
the utterance ends at the end of the file. (default -1)
label_lists (LabelList, list): A single or multiple label-lists.
Attributes:
label_lists (dict): A dictionary containing label-lists with the label-list-idx as key.
"""
__slots__ = ['idx', 'file', 'issuer', 'start', 'end', 'label_lists']
def __init__(self, idx, file, issuer=None, start=0, end=-1, label_lists=None):
self.idx = idx
self.file = file
self.issuer = issuer
self.start = start
self.end = end
self.label_lists = {}
if label_lists is not None:
self.set_label_list(label_lists)
if self.issuer is not None:
self.issuer.utterances.add(self)
@property
def end_abs(self):
"""
Return the absolute end of the utterance relative to the signal.
"""
if self.end == -1:
return self.file.duration
else:
return self.end
@property
def duration(self):
"""
Return the absolute duration in seconds.
"""
return self.end_abs - self.start
[docs] def num_samples(self, sr=None):
"""
Return the number of samples.
Args:
sr (int): Calculate the number of samples with the given sampling-rate.
If None use the native sampling-rate.
Returns:
int: Number of samples
"""
native_sr = self.sampling_rate
num_samples = units.seconds_to_sample(self.duration, native_sr)
if sr is not None:
ratio = float(sr) / native_sr
num_samples = int(np.ceil(num_samples * ratio))
return num_samples
#
# Signal
#
[docs] def read_samples(self, sr=None, offset=0, duration=None):
"""
Read the samples of the utterance.
Args:
sr (int): If None uses the sampling rate given by the file, otherwise resamples to the given sampling rate.
offset (float): Offset in seconds to read samples from.
duration (float): If not None read only this number of seconds in maximum.
Returns:
np.ndarray: A numpy array containing the samples as a floating point (numpy.float32) time series.
"""
read_duration = None
if self.end >= 0:
read_duration = self.duration
if offset > 0:
read_duration -= offset
if duration is not None:
read_duration = min(duration, read_duration)
return self.file.read_samples(sr=sr, offset=self.start + offset, duration=read_duration)
@property
def sampling_rate(self):
"""
Return the sampling rate.
"""
return self.file.sampling_rate
#
# Labels
#
[docs] def set_label_list(self, label_lists):
"""
Set the given label-list for this utterance. If the label-list-idx is not set, ``default`` is used.
If there is already a label-list with the given idx, it will be overriden.
Args:
label_list (LabelList, list): A single or multiple label-lists to add.
"""
if isinstance(label_lists, label.LabelList):
label_lists = [label_lists]
for label_list in label_lists:
if label_list.idx is None:
label_list.idx = 'default'
label_list.utterance = self
self.label_lists[label_list.idx] = label_list
[docs] def all_label_values(self, label_list_ids=None):
"""
Return a set of all label-values occurring in this utterance.
Args:
label_list_ids (list): If not None, only label-values from label-lists with an id contained in this list
are considered.
Returns:
set: A set of distinct label-values.
"""
values = set()
for label_list in self.label_lists.values():
if label_list_ids is None or label_list.idx in label_list_ids:
values = values.union(label_list.label_values())
return values
[docs] def label_count(self, label_list_ids=None):
"""
Return a dictionary containing the number of times, every label-value in this utterance is occurring.
Args:
label_list_ids (list): If not None, only labels from label-lists with an id contained in this list
are considered.
Returns:
dict: A dictionary containing the number of occurrences with the label-value as key.
"""
count = collections.defaultdict(int)
for label_list in self.label_lists.values():
if label_list_ids is None or label_list.idx in label_list_ids:
for label_value, label_count in label_list.label_count().items():
count[label_value] += label_count
return count
[docs] def label_total_duration(self, label_list_ids=None):
"""
Return a dictionary containing the number of seconds, every label-value is occurring in this utterance.
Args:
label_list_ids (list): If not None, only labels from label-lists with an id contained in this list
are considered.
Returns:
dict: A dictionary containing the number of seconds with the label-value as key.
"""
duration = collections.defaultdict(float)
for label_list in self.label_lists.values():
if label_list_ids is None or label_list.idx in label_list_ids:
for label_value, label_duration in label_list.label_total_duration().items():
duration[label_value] += label_duration
return duration