Joint Speaker Counting, Speech Recognition, and Speaker Identification for Overlapped Speech of Any Number of Speakers
Table 1: SER (%), WER (%), and SA-WER (%) for baseline systems and proposed method. The number of profiles per test audio was 8. Each profile was extracted by using 2 utterances (15 sec on average). For random speaker assignment experiment (3rd row), averages of 10 trials were computed. No LM was used in the evaluation.
['ModelEval Set', '1-speaker SER', '1-speaker WER', '1-speaker  [BOLD] SA-WER', '2-speaker-mixed SER', '2-speaker-mixed WER', '2-speaker-mixed  [BOLD] SA-WER', '3-speaker-mixed SER', '3-speaker-mixed WER', '3-speaker-mixed  [BOLD] SA-WER', 'Total SER', 'Total WER', 'Total  [BOLD] SA-WER']
Baseline results The first row corresponds the conventional single-speaker ASR based on AED. As expected, the WER was significantly degraded for overlapped speech. The second row shows the result of the SOT-ASR system that was used for initializing the proposed method in training. SOT-ASR significantly improved the WER for all evaluation settings.