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This paper presents a template-based system for speaker independent key word spotting (KWS) in continuous speech that can help in automatic analysis, indexing, search and retrieval of user generated videos by content. Extensive experiments on clean speech confirm that the proposed approach is superior to a HMM approach when applied to noisy speech with different signal-to-noise ratio (SNR) levels...
This paper presents a robust keyword detection system for criminal scene analysis. The system follows the classical keyword spotting framework. A universal background model is designed and served as the filler model and anti-word model in keyword recognition and verification, respectively. Specifically, we analyze the
This study presents keyword recognition evaluation on a new corpus named ProfLifeLog. ProfLifeLog is a collection of data captured on a portable audio recording device called the LENA unit. Each session in ProfLifeLog consists of 10+ hours of continuous audio recording that captures the work day of the speaker (person
some manufacturing and logistical operations, or for information retrieval from large audio archives. We investigate the use of three keyword spotting techniques and compare them with a classic large vocabulary sp eech reco gnit ion sy st em. To evaluat e t heir performance, we specified and studied two model applications
, by analysing the presence of distress keywords. An experimental protocol was defined and then this system has been evaluated in uncontrolled conditions in which heterogeneous speakers were asked to utter predetermined sentences in the HIS. The results of this experiment, where ten subjects were involved, are presented
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