Title :
The IBM keyword search system for the DARPA RATS program
Author :
Mangu, Lidia ; Soltau, Hagen ; Hong-Kwang Kuo ; Saon, George
Author_Institution :
IBM T. J. Watson Res. Center, Yorktown Heights, NY, USA
Abstract :
The paper describes a state-of-the-art keyword search (KWS) system in which significant improvements are obtained by using Convolutional Neural Network acoustic models, a two-step speech segmentation approach and a simplified ASR architecture optimized for KWS. The system described in this paper had the best performance in the 2013 DARPA RATS evaluation for both Levantine and Farsi.
Keywords :
neural nets; query processing; speech recognition; ASR architecture; DARPA RATS program; IBM keyword search system; KWS system; automatic speech recognition; convolutional neural network acoustic model; speech segmentation; Acoustics; Decoding; Hidden Markov models; Keyword search; Lattices; Rats; Speech; audio indexing; keyword spotting; spoken term detection; system combination;
Conference_Titel :
Automatic Speech Recognition and Understanding (ASRU), 2013 IEEE Workshop on
Conference_Location :
Olomouc
DOI :
10.1109/ASRU.2013.6707730
