SPEAKER-AWARE SPEECH-TRANSFORMER
Table 2: CER[%] for frame-level and utterance-level soft speaker embedding on test set of AISHELL-1.
['#I-vectors', 'frame-level', 'utterance-level']
We tried three different settings for the number of i-vectors in SKB: 50, 100, and 200. It’s obvious that the utterance-level speaker embedding performs worse than the frame-level one for all the three settings. This is consistent with our intuition. Speaker’s mood, speed or tone can not keep constant over time in one utterance. Frame-level speaker embedding is able to calculate a reasonable speaker vector according to the acoustic features of current time step, thus it’s more effective than utterance-level embedding to catch the variations over time.