In this paper we present a novel approach to acoustic model training for non-audible murmur (NAM) recognition using normal speech data transformed into NAM data. NAM is extremely ...
In this paper we propose a feedforward neural network for syllable recognition. The core of the recognition system is based on a hierarchical architecture initially developed for ...
Xavier Domont, Martin Heckmann, Heiko Wersing, Fra...
Recently, a novel and structural representation of speech was proposed [1, 2], where the inevitable acoustic variations caused by nonlinguistic factors are effectively removed fro...
The acceleration of acoustic likelihood calculation has been an important research issue for developing practical speech recognition systems. And there are various specification ...
There has been increasing interest recently in meeting understanding, such as summarization, browsing, action item detection, and topic segmentation. However, there is very limite...