d733b902552295be41b1f88c8343b5e7b4ff8a9b,TTS/speaker_encoder/dataset.py,MyDataset,__parse_items,#MyDataset#,53

Before Change

        
        Find unique speaker ids and create a dict mapping utterances from speaker id
        
        speakers = list({item[-1] for item in self.items})
        self.speaker_to_utters = {}
        self.speakers = []
        for speaker in speakers:

After Change

        for i in self.items:
            path_ = i[1]
            speaker_ = i[2]
            if speaker_ in self.speaker_to_utters.keys():
                self.speaker_to_utters[speaker_].append(path_)
            else:
                self.speaker_to_utters[speaker_] = [path_, ]

            if self.skip_speakers:
                self.speaker_to_utters = {k: v for (k, v) in self.speaker_to_utters.items() if
                                          len(v) >= self.num_utter_per_speaker}

Instances