emvoice.frames

Store audio and voice feature frames.

Module Contents

Classes

BaseFrames

Create and store signal frames.

class emvoice.frames.BaseFrames(frames: numpy.ndarray, sr: int, frame_len: int, hop_len: int, center: bool = True, pad_mode: str = 'constant')[source]

Create and store signal frames.

A frame is an (overlapping, padded) slice of a signal for which higher-order features can be computed.

Parameters:
  • frames (numpy.ndarray) – Signal frames. The first dimension should be the number of frames.

  • sr (int) – Sampling rate.

  • frame_len (int) – Number of samples per frame.

  • hop_len (int) – Number of samples between frame starting points.

  • center (bool, default=True) – Whether the signal has been centered and padded before framing.

  • pad_mode (str, default='constant') – How the signal has been padded before framing. See numpy.pad(). Uses the default value 0 for ‘constant’ padding.

See also

librosa.util.frame

property idx: numpy.ndarray[source]

Frame indices (read-only).

property ts: numpy.ndarray[source]

Frame timestamps (read-only).

classmethod from_signal(sig_obj: emvoice.signal.BaseSignal, frame_len: int, hop_len: Optional[int] = None, center: bool = True, pad_mode: str = 'constant')[source]

Create frames from a signal.

Parameters:
  • sig_obj (BaseSignal) – Signal object.

  • frame_len (int) – Number of samples per frame.

  • hop_len (int, optional, default=None) – Number of samples between frame starting points. If None, uses frame_len // 4.

  • center (bool, default=True) – Whether to center the frames and apply padding.

  • pad_mode (str, default='constant') – How the signal is padded before framing. See numpy.pad(). Uses the default value 0 for ‘constant’ padding. Ignored if center=False.