Sentence examples for text speakers from inspiring English sources

Chafe (1988) suggests that, for the same written text, speakers are limited to about 5.7 words per intonation contour as opposed to the 8.9 words in a punctuation unit – an increase of about 50%%.

By focusing on the understanding of a contemporaneous "reasonable reader," Gorsuch's Originalism confuses audience understanding of speaker text with speaker meaning itself.

Two researchers lead each focus group, one to facilitate discussion and the other to take notes that link text to speakers and highlight points of consensus or disagreement and issues that draw strong emotional responses such as anger, fear or anxiety.

Text independent speaker verification experiments are conducted on the NIST 2010 speaker recognition evaluation (SRE) data set[8].

Complete letter text: Dear Speaker Boehner, With five days until our nation faces an unprecedented financial crisis, we need to work together to ensure that our nation does not default on our obligations for the first time in our history.

The sleek CDMA handset includes the practical features one needs such as text messaging, speaker phone, calendar, a personalized voice reminder and an alarm clock.

Using transcripts available at the American Presidency Project of the University of California, we wrote a program to sort the text by speaker and count the number of times words appear.

We attempt to make a preliminary beginning to combine the advantages of traditional MAP adaptation in text-dependent speaker verification and i-vector-based framework in text-independent speaker verification.

The systems of textual relations are naturally pivotal to register identities: since there is no text without a speaker, the speaker is always 'there' both as a material presence in the material situational setting and as a semantic presence inscribed in the text.

The model was tested on two audio visual speech processing tasks, namely speech recognition and text-dependent speaker verification, both using the M2VTS database.

This paper provides an efficient approach for text-independent speaker identification using a fused Mel feature sets and Gaussian Mixture Modeling (GMM).