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| from speaker_encoder.data_objects.random_cycler import RandomCycler | |
| from speaker_encoder.data_objects.utterance import Utterance | |
| from pathlib import Path | |
| # Contains the set of utterances of a single speaker | |
| class Speaker: | |
| def __init__(self, root: Path): | |
| self.root = root | |
| self.name = root.name | |
| self.utterances = None | |
| self.utterance_cycler = None | |
| def _load_utterances(self): | |
| with self.root.joinpath("_sources.txt").open("r") as sources_file: | |
| sources = [l.split(",") for l in sources_file] | |
| sources = {frames_fname: wave_fpath for frames_fname, wave_fpath in sources} | |
| self.utterances = [Utterance(self.root.joinpath(f), w) for f, w in sources.items()] | |
| self.utterance_cycler = RandomCycler(self.utterances) | |
| def random_partial(self, count, n_frames): | |
| """ | |
| Samples a batch of <count> unique partial utterances from the disk in a way that all | |
| utterances come up at least once every two cycles and in a random order every time. | |
| :param count: The number of partial utterances to sample from the set of utterances from | |
| that speaker. Utterances are guaranteed not to be repeated if <count> is not larger than | |
| the number of utterances available. | |
| :param n_frames: The number of frames in the partial utterance. | |
| :return: A list of tuples (utterance, frames, range) where utterance is an Utterance, | |
| frames are the frames of the partial utterances and range is the range of the partial | |
| utterance with regard to the complete utterance. | |
| """ | |
| if self.utterances is None: | |
| self._load_utterances() | |
| utterances = self.utterance_cycler.sample(count) | |
| a = [(u,) + u.random_partial(n_frames) for u in utterances] | |
| return a | |