Against the baseline HMM embed model, which is trained on full utterances, however, not all ensemble methods perform so well.
Her cheek, occupying the central space in the photograph, seems full with utterance.
Table 2 Category of the REVERB challenge speech recognition task Type Processing scheme Full batch, utterance-based, real-time Training data of acoustic model Own dataset, multi-condition, clean Recognizer type own recognizer, Challenge baseline recognizer Number of channels used 1, 2, 8 Italicized data denotes the category to which this paper belongs.
In order to be sure that the speech segment contains the full targeted speech utterance even if only a part of the phonetic string is spotted (due to smart queries), we enlarge the segment before and after the spotted area.
We trained networks on clean data only, as well as on the full set of utterances in the multi-condition training set.
The mapping function was updated every time that reverberation conditions changed and the ICDF (Phi _{y}^{-1}) of observations were collected from the full batch of utterances in each test condition.
"It is powerful obsessive stuff, intensely theatrical, not always disciplined but always wildly poetic, full of stage images and utterances replete with insidious suggestiveness".
Another difference between utterance-based versus full batch processing is that we are able to decode with MLIFD features in full batch processing.
Unlike for our workshop paper [12] that covered the 1ch ASR task in both the full batch processing and the utterance-based batch processing mode, here we focus on the 1ch scenarios only in the utterance-based batch processing mode for which each utterance is processed separately, since this provides the maximum potential for real-time applications.
It is important to note that the recall rates are not influenced by the query reduction, with an utterance spotted by the full phonetic string being necessarily spotted by any of its substrings.
