Constrained Output Embeddings for End-to-End Code-Switching Speech Recognition with Only Monolingual Data
Table 3: The MER performance after applying the language model during the decoding stages
['Model', 'Decoder LM', 'MER (%) test [ITALIC] man', 'MER (%) test [ITALIC] eng']
The state-of-the-art results in ASR are usually obtained by employing a language model (LM). To examine whether proposed constraints are complementary with LM, we employed LM during the decoding stage. Obtained MER improvements show that proposed constraints and LM complement each other. Moreover, the proposed method benefits from the LM more than the strong baseline model.