Toward Low-Cost End-to-End Spoken Language Understanding. (arXiv:2207.00352v1 [cs.CL])

Recent advances in spoken language understanding benefited from
Self-Supervised models trained on large speech corpora. For French, the
LeBenchmark project has made such models available and has led to impressive
progress on several tasks including spoken language understanding. These
advances have a non-negligible cost in terms of computation time and energy
consumption. In this paper, we compare several learning strategies trying to
reduce such cost while keeping competitive performance. At the same time we
propose an extensive analysis where we …

arxiv cost language spoken language understanding understanding