3 accepted papers
We propose the Chunkwise Aligner, a novel architecture for streaming automatic speech recognition (ASR). While the Transducer is the standard model for streaming ASR, its training is costly due to the need to compute all possible audio-label alignments. The recently introduced Aligner reduces this c…
Unlike modern streaming Automatic Speech Recognition (ASR) systems which segment speech into fixed-length chunks for decoding, humans perceive speech in variable-length units of information. This paper proposes a novel method that leverages self-information, a measure of the information contained wi…
This paper introduces CIF-RNNT, a model that incorporates Continuous Integrate-and-Fire into RNN-Transducers (RNNTs) for streaming ASR via acoustic word embeddings (AWEs). CIF can dynamically compress long sequences into shorter ones, while RNNTs can produce multiple symbols given an input vector. W…