Sentence examples for most often recognition from inspiring English sources

Exact(1)

Most often, recognition was informal, consisting of the acknowledgement that corridors existed and were subject to some degree of customary regulation.

Similar(59)

Many diverse RBPs bind these intronic elements, most often to repress recognition of nearby splice sites [ 1].

Instead, fungi most often use the recognition of mating-pheromone peptides, which have been detected in all fungal lineages (Kothe, 2008).

The presented method is closely related to other works that consider observation vectors as uncertain for decoding purposes, most often for noisy speech recognition [1 4], but in some cases also for speech recognition in multitalker conditions, as, for example, [5, 6], or [7] in conjunction with speech segregation via binary masking (see, e.g. [8, 9]).

That's the kind of mild laughter the bland feature-film version of "Hey Arnold!," the latest Nickelodeon cartoon to make the jump to movie screens, will probably get most often -- chuckles of recognition from the kids who have watched his adventures on his series.

Nadeau and Sekine (2007: 8) list punctuation among the "features most often used for the recognition and classification of named entities".

"If you talk about the unsung heroes of our season, he's probably been the guy who came through for us the most often and got the least amount of recognition for it," Carlisle said.

Lowry was the individual to have rejected recognition from the Queen the most often, turning down a total of five honours, including a knighthood.

For decades, however, Kusama failed to get the same critical recognition as her male contemporaries, most often only being acknowledged for work that was blatantly sexual or extreme. .

(p. 643) Recognition that TE carriage might most often be selfish at the genomic level, detrimental if not neutral at the organismal and perhaps sometimes beneficial at the species level, replaces "either/or" thinking with a more realistic pluralist ontology.

The proposed modelling approach is very similar to the one used in standard speech recognition, where basic HMM units (the most often acoustic phoneme models) are trained and are then connected according to the dictionary and some grammar (language model) to obtain a recognition network, along which recognition can be interpreted also as an alignment process.

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