Sentence examples for switchboard model from inspiring English sources

Implicit in the mosaic hypothesis is a kind of telephone switchboard model of the brain as a machine in which the electrical activity is strictly confined to separate pathways of neurons that are well insulated (isolated) from one another.

We spoke to Domanovic about switchboards, 3D modelling, and why women can't (yet) time travel.

This common business model has been documented by Switchboard and their implementation of MDNet, a nationwide mobile phone CUG for physicians in Ghana and Liberia, separately.

Table 1 Corpora used for training various components of the system   Switchboard NIST SRE04 NIST SRE05 NIST SRE06 Tel Tel Tel Mic Tel Mic UBM X T X X X D X X X PLDA    D X X X       PLDA model X X X X Whitening X X X X X X G-rank-norm G-rank-norm G-rank-norm X X X X X X s-norm s-norm X X X Xic' refer Thetermshone (landline or mobile) and microphone channel recordings.

By that time, nearly all typists, receptionists, stenographers, file clerks, and switchboard operators were women, many of them trained in schools modelled on the one that Katharine Gibbs had opened in Providence in 1911.

The pair also noted that in the last 100 years, the Model T has given way to Teslas, and switchboards have given way to incredible smart phones.

Using a much larger 2100-hour training corpus (combining Switchboard and Fisher) we examine the performance of very large DNN models – with up to ten times more parameters than those typically used in speech recognition systems.

Perplexity evaluation on a public corpus is performed in Section 3. Our proposed model is further evaluated on the Wall Street Journal (WSJ) and Switchboard speech-to-text tasks in Sections 4 and 5. Finally, Section 6 concludes this paper and gives the future work.

We apply our proposed method to a well-tuned context-dependent deep neural network hidden Markov model (CD-DNN-HMM) speech recognition system on the English-Switchboard speech-to-text task.

We apply our proposed method to a well-tuned context-dependent deep neural network hidden Markov model (CD-DNN-HMM) speech recognition system on the English-Switchboard phone-call speech-to-text task, where both FNNLM and RNNLM are trained to demonstrate our method.

Trigram language models trained on Switchboard-1 and Fisher transcripts are interpolated and then pruned, giving a language model with 323K trigrams and 552K bigrams.