Sentence examples for segment speech from inspiring English sources

Phonological awareness refers to the ability to segment speech into smaller phonological units and analyze and manipulate these units.

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.

Such transitional probabilities are particularly informative regarding structural boundaries, and adults and infants appear to exploit them in order to segment speech and music alike (Aslin, Saffran, & Newport, 1998; Saffran, Aslin, & Newport, 1996; Saffran, Johnson, Aslin, & Newport, 1999; Saffran, Newport, & Aslin, 1996).

Concerning the first step of word extraction from speech, when no semantic or prosodic information is available, it has been suggested that listeners can use a general statistical learning mechanism to segment speech based on adjacent [2] and non-adjacent statistical dependencies between syllables [11].

Infants also use this feature to correctly segment speech streams.

In other words, speakers of stress-timed languages segment speech in feet, speakers of syllable-timed languages in syllables, and speakers of mora-timed languages in morae (Cutler et al. 1986; Otake et al. 1993; Mehler et al. 1996).

The stream, however, auditorily appears to be segmented (speech in an unfamiliar language often seems like an unsegmented stream).

First, the VAD of the Voicebox [130] tool is applied to segment the speech signal into speech segments.

In QbE STD, we consider the scenario in which the user has found a segment of speech which contains terms of interest within a speech data repository, and their purpose is to find similar speech segments within that repository.

The aim of language recognition is to determine the language spoken in a given segment of speech.

In the implementation of the DS beamformer, we segmented the speech utterances into segments of 64 ms long with 75%% overlap.