Sentence examples for speech methodologies from inspiring English sources

This paper briefly reviews current silent speech methodologies for normal and disabled individuals.

For speech movements, this methodology enables us to extract at least six components once the head movements have been removed.

In our previous paper [16], we applied TF decomposition feature extraction methodology to speech signals in order to automatically identify and measure the speech pathology problem.

Based on the challenge task, and relying on well-proven methodologies from the speech recognition domain, we derive test scenarios with realistic noise and reverberation conditions, including matched as well as mismatched condition training.

In this article, a novel technique based on the empirical mode decomposition methodology for processing speech features is proposed and investigated.

This method was first introduced in the keynote speech titled "Reflection on the Methodology of Communication Studies" in The 8th Chinese Internet Research Conference Peking Universityy, June 29 30, 2010).

This work proposes a methodology to learn a speech representation from data by optimising a filter bank, in order to improve results in the classification of stressed speech.

A general methodology followed in whispered speech recognition systems is to segment speech at the whisper boundaries and subsequently use statistical models like the hidden Markov model (HMM) to perform recognition.

This design methodology is demonstrated using a speech recognition system.

First, the most relevant studies in speech watermarking are reviewed, and the applied methodology is then discussed.

This paper presents a methodology that uses phonological features, automatic speech alignment (based on acoustic models trained with normal speech), context-dependent speaker feature extraction, and intelligibility prediction based on a small model that can be trained on pathological speech samples.