Streaming Transformer-based Acoustic Models Using Self-attention with Augmented Memory
Table 3: Performance of different models on LibriSpeech. “Str” stands for streamable, specifying if a model is a streamable one.
['#Param', 'Str', 'Model', 'test-clean', 'test-other']
For a fair comparison on latency, corresponding models of similar look-ahead window are compared. The first block compares models with about 40M parameters. The transformer-XL baseline used a segment length of 128, which is identical to that of the proposed model. The TRTrf baseline used a context of 3 in each layer, resulting a look-ahead window of 0.72 second. The proposed augmented memory transformer outperformed all the streamable baselines.