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The article describes a system that uses real time measurements of the vocal tract to drive a voice-replacement system for post-laryngectomy patients. Based on a thermoformed acquisition helmet, miniature ultrasound machine, and video camera, and incorporating Hidden Markov Model speech recognition, the device has been tested on three speakers, one of whom has undergone a total laryngectomy. Results...
LVCSR systems are usually based on continuous density HMMs, which are typically implemented using Gaussian mixture distributions. Such statistical modeling systems tend to operate slower than real-time, largely because of the heavy computational overhead of the likelihood evaluation. The objective of our research is to investigate approximate methods that can substantially reduce the computational...
The paper proposes a human-computation-based scheme for transcribing Southern Min speech corpora. The core idea is to implement a Web-based language learning system to collect orthographic and phonetic labels from a large amount of language learners and choose the commonly input labels as the transcriptions of the corpora. It is essentially a technology of distributed knowledge acquisition. Some computer-aided...
Most state-of-the-art LVCSR systems are based on continuous density HMMs, which are typically implemented using Gaussian mixture distributions. Such statistical modeling systems usually operate slower than real-time, largely because of the heavy computational overhead of the likelihood computation. The objective of our research is to investigate application of modern SIMD technology to speed up the...
A fast likelihood computation approach called dynamic Gaussian selection (DGS) is proposed for HMM-based continuous speech recognition. DGS approach is a one-pass search technique which generates a dynamic shortlist of Gaussians for each state during the procedure of likelihood computation. The shortlist consists of the Gaussians which make prominent contribution to the likelihood. In principle, DGS...
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