SPEAKER-AWARE SPEECH-TRANSFORMER
Table 3: CER[%] for ST, SAST with 100 i-vectors in AISHELL-1 and attaching i-vector to model (input or output of encoder) directly. Gains are relative to our ST baselilne on test set.
['Models', 'Dev', 'Test', 'Gain']
For soft speaker embedding (SAST model), we choose the best settings according to the findings in previous three experiments: the number of i-vectors in SKB is 100, SAM is located at the highest encoder block, and speaker embedding is performed at the frame-level. As for the hard embedding, two approaches are tried. The first method is named as input of ST +⃝ The second one is called output of encoder + ⃝ i-vector, in which the output of highest encoder block at each time step is spliced with the i-vector of the corresponding speaker. Compared with hard embedding, the soft speaker embedding performed by SAM empowers SAST to generalize better to unseen speakers.