Source code for nnmnkwii.datasets.cmu_arctic

from __future__ import absolute_import, print_function, with_statement

from os import listdir
from os.path import isdir, join, splitext

import numpy as np
from nnmnkwii.datasets import FileDataSource

# List of available speakers.
available_speakers = [

def _name_to_dirname(name):
    assert len(name) == 3
    return join("cmu_us_{}_arctic".format(name), "wav")

[docs]class WavFileDataSource(FileDataSource): """Wav file data source for CMU Arctic dataset. The data source collects wav files from CMU Arctic. Users are expected to inherit the class and implement ``collect_features`` method, which defines how features are computed given a wav file path. Args: data_root (str): Data root. speakers (list): List of speakers to find. Supported names of speaker are ``aew``, ``ahw``, ``aup``, ``awb``, ``axb``, ``bdl``, ``clb``, ``eey``, ``fem``, ``gka``, ``jmk``, ``ksp``, ``ljm``, ``lnh``, ``rms``, ``rxr``, ``slp``, ``slt`` . labelmap (dict[optional]): Dict of speaker labels. If None, it's assigned as incrementally (i.e., 0, 1, 2) for specified speakers. max_files (int): Total number of files to be collected. Attributes: labels (numpy.ndarray): Speaker labels paired with collected files. Stored in ``collect_files``. This is useful to build multi-speaker models. """ def __init__(self, data_root, speakers, labelmap=None, max_files=None): for speaker in speakers: if speaker not in available_speakers: raise ValueError( "Unknown speaker '{}'. It should be one of {}".format( speaker, available_speakers ) ) self.data_root = data_root self.speakers = speakers if labelmap is None: labelmap = {} for idx, speaker in enumerate(speakers): labelmap[speaker] = idx self.labelmap = labelmap self.max_files = max_files self.labels = None
[docs] def collect_files(self): """Collect wav files for specific speakers. Returns: list: List of collected wav files. """ speaker_dirs = list( map(lambda x: join(self.data_root, _name_to_dirname(x)), self.speakers) ) paths = [] labels = [] if self.max_files is None: max_files_per_speaker = None else: max_files_per_speaker = self.max_files // len(self.speakers) for (i, d) in enumerate(speaker_dirs): if not isdir(d): raise RuntimeError("{} doesn't exist.".format(d)) files = [join(speaker_dirs[i], f) for f in listdir(d)] files = list(filter(lambda x: splitext(x)[1] == ".wav", files)) files = sorted(files) files = files[:max_files_per_speaker] for f in files: paths.append(f) labels.append(self.labelmap[self.speakers[i]]) self.labels = np.array(labels, dtype=np.int32) return paths
# For compat, remove this after v0.1.0 CMUArcticWavFileDataSource = WavFileDataSource