c6e474fb13be0362c6f239f81c128f6d4c751da4,pyannote/audio/labeling/tasks/resegmentation.py,Resegmentation,apply,#Resegmentation#Any#Any#,247

Before Change

        labels = batch_generator.specifications["y"]["classes"][1:]

        // features sliding window
        window = self.feature_extraction.sliding_window

        if self.keep_sad:

            // sequence of most likely speaker index
            // (even when non-speech is the most likely class)
            best_speaker_indices = np.argmax(scores[:, 1:], axis=1) + 1

            // reconstruct annotation
            new_hypothesis = one_hot_decoding(
                best_speaker_indices, window, labels=labels)

            // revert non-speech regions back to original
            speech = hypothesis.get_timeline().support()
            new_hypothesis = new_hypothesis.crop(speech)

        else:

            // sequence of most likely class index (including 0=non-speech)
            best_class_indices = np.argmax(scores, axis=1)

            // reconstruct annotation
            new_hypothesis = one_hot_decoding(
                best_class_indices, window, labels=labels)

        new_hypothesis.uri = hypothesis.uri
        return new_hypothesis

After Change

        // speaker labels
        labels = batch_generator.specifications["y"]["classes"][1:]

        return self._decode(current_file, hypothesis, scores, labels)


class ResegmentationWithOverlap(Resegmentation):
    Re-segmentation with overlap

Instances