Symposium on Machine Learning in Speech and Language Processing (MLSLP)
Portland, Oregon, USA
The acoustic models in state-of-the-art speech recognition systems are based on phones in context that are represented by hidden Markov models. This modeling approach may be insufficient to model long-span acoustic context. Exemplar-based approaches may be an attractive alternative to this conventional approach. In this talk, we will discuss a general rescoring framework based on conditional random fields and show how to do exemplar-based speech recognition within this framework, with the focus on massive, noisy data. Experimental results for the Voice Search and the YouTube tasks are presented and analyzed.
Bibliographic reference. Heigold, Georg (2012): "Exemplar-based speech recognition in a rescoring approach", In MLSLP-2012 (abstract).