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keywords which are used as features to distinguish different sports. Finally, based on the keyword spotting (KWS) results and specific keywords selected for each kind of sports, a score ranking strategy is designed for conducting classification automatically. For robust KWS in our system, adaptation techniques for acoustic
challenging problem. Generic methods for sentiment extraction generally use transcripts from a speech recognition system, and process the transcript using text-based sentiment classifiers. In this study, we show that this baseline system is suboptimal for audio sentiment extraction. Alternatively, new architecture using keyword
In this paper we investigate various techniques in order to build effective speech to text (STT) and keyword search (KWS) systems for low resource conversational speech. Subword decoding and graphemic mappings were assessed in order to detect out-of-vocabulary keywords. To deal with the limited amount of transcribed
automatic speech recognisers using HMM/GMM, SGMM and DNN/HMM acoustic models as keyword spotters. We present the first results indicating promising performance of the radio-browsing system.
This work proposes a voice-activity home care system which can construct a life log associated with voices at home. Accordingly, the techniques of sound-pressure-level calculation, abnormal sound detection, noise reduction, text-independent speaker recognition and keyword spotting are developed. In abnormal sound
This paper extends recent research on training data selection for speech transcription and keyword spotting system development. Selection techniques were explored in the context of the IARPA-Babel Active Learning (AL) task for 6 languages. Different selection criteria were considered with the goal of improving over a
prototype system demonstrates our latest development on automatic speech recognition, keyword spotting, personalized text-to-speech synthesis and visual speech synthesis. The second demo exhibits a virtual concert with immersive audio effects. Through our virtual auditory technology, wearing simple earphones, listeners are
recognition using audio and visual cues. The novelty lies in putting together the tasks such that they can provide relevant information to one another. We evaluate the performance of our system and present results for tasks such as keyword spotting and tracking re-identification on real-world meeting scenes collected in our
We examine the task of spoken term detection in Chinese spontaneous speech with a lattice-based approach. We first compare lattices generated with different units: word, character, tonal and toneless syllables, and also lattices converted from one unit to another unit. Then we combine lattices from multiple systems into a single lattice. By fully exploiting the redundant information in the combined...
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