5a1dba682a5eccd4f0854553c07cd2b21909f1ec,pyannote/audio/labeling/tasks/resegmentation.py,Resegmentation,_decode,#Resegmentation#Any#Any#Any#Any#,312

Before Change

            // K = 1 <~~> only non-speech
            // K = 2 <~~> just one speaker
            if K < 3:
                return hypothesis

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

            // reconstruct annotation
            new_hypothesis = one_hot_decoding(

After Change

        N, K = scores.data.shape

        if self.allow_overlap:
            active_speakers = np.exp(scores.data > 0.5)

        else:
            if self.lock_speech:
                active_speakers = np.argmax(scores.data, axis=1)

Instances