Source code for openspeech.data.audio.melspectrogram.melspectrogram

# MIT License
#
# Copyright (c) 2021 Soohwan Kim and Sangchun Ha and Soyoung Cho
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.

import numpy as np
from omegaconf import DictConfig

from ... import register_audio_feature_transform
from ...audio.melspectrogram.configuration import MelSpectrogramConfigs
from ....utils import LIBROSA_IMPORT_ERROR


@register_audio_feature_transform("melspectrogram", dataclass=MelSpectrogramConfigs)
class MelSpectrogramFeatureTransform(object):
    r"""
    Create MelSpectrogram for a raw audio signal. This is a composition of Spectrogram and MelScale.

    Args:
        configs (DictConfig): configuraion set

    Returns:
        Tensor: A mel-spectrogram feature. The shape is ``(seq_length, num_mels)``
    """
    def __init__(self, configs: DictConfig) -> None:
        super(MelSpectrogramFeatureTransform, self).__init__()
        try:
            import librosa
        except ImportError:
            raise ImportError(LIBROSA_IMPORT_ERROR)
        self.sample_rate = configs.audio.sample_rate
        self.num_mels = configs.audio.num_mels
        self.n_fft = int(round(configs.audio.sample_rate * 0.001 * configs.audio.frame_length))
        self.hop_length = int(round(configs.audio.sample_rate * 0.001 * configs.audio.frame_shift))
        self.function = librosa.feature.melspectrogram
        self.power_to_db = librosa.power_to_db

    def __call__(self, signal: np.ndarray) -> np.ndarray:
        """
        Provides feature extraction

        Inputs:
            signal (np.ndarray): audio signal

        Returns:
            feature (np.ndarray): feature extract by sub-class
        """
        melspectrogram = self.function(
            y=signal,
            sr=self.sample_rate,
            n_mels=self.num_mels,
            n_fft=self.n_fft,
            hop_length=self.hop_length,
        )
        melspectrogram = self.power_to_db(melspectrogram, ref=np.max)
        return melspectrogram