A KEYWORD SEARCH SYSTEM USING OPEN SOURCE SOFTWARE

被引：0

作者：

Trmal, Jan ^{[1
]}

Chen, Guoguo ^{[1
]}

Povey, Dan ^{[1
]}

Khudanpur, Sanjeev ^{[1
]}

Ghahremani, Pegah ^{[1
]}

Zhang, Xiaohui ^{[1
]}

Manohar, Vimal ^{[1
]}

Liu, Chunxi ^{[1
]}

Jansen, Aren ^{[1
]}

Klakow, Dietrich ^{[2
]}

Yarowsky, David ^{[1
]}

Metze, Florian ^{[3
]}

机构：

[1] Johns Hopkins Univ, Baltimore, MD 21218 USA

[2] Univ Saarland, Saarbrucken, Germany

[3] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA

来源：

2014 IEEE WORKSHOP ON SPOKEN LANGUAGE TECHNOLOGY SLT 2014 | 2014年

关键词：

Kaldi; spoken term detection; keyword search; speech recognition; deep neural networks; pitch; IARPA BABEL; OpenKWS; MODELS;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Provides an overview of a speech-to-text (STT) and keyword search (KWS) system architecture build primarily on the top of the Kaldi toolkit and expands on a few highlights. The system was developed as a part of the research efforts of the Radical team while participating in the IARPA Babel program. Our aim was to develop a general system pipeline which could be easily and rapidly deployed in any language, independently on the language script and phonological and linguistic features of the language.

引用

页码：530 / 535

页数：6

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