Sentence examples for phonetic training from inspiring English sources

Therefore, the experts in this particular field may have gone through phonetic training with varying emphases.

Due to the lack of large enough singing databases to train a recognizer for singing, we use a phonetic recognizer trained on speech and adapt it to singing, as presented in Section 2.3.

He has a talent for sardonic aphorism — "Hope is a gateway drug, don't do it" — and an ear for phonetic intrigue: "Snipers trained their scopes, muzzles crackling next to the squatting cornice gargoyles and the shells hopping on the rooftop tar".

Due to the lack of large enough singing databases to train a singing recognizer, we used a phonetic recognizer that was trained on speech and applied speaker adaptation techniques to adapt the models to singing voice.

During training, the phonetic contexts are determined for the decoding questions from the forced alignments of the training data.

It is shown that acoustic models for broad phonetic categories that are trained on neutral speech produce emotional speech with significantly different likelihood scores, which can be used to discriminate emotions.

The phoneme-level language models were trained using the phonetic transcriptions of the speech database that was used for training the acoustic models.

Voice Signal Technologies, for example, makes software for cellphone manufacturers that converts text information into phonetic information without any user training.

The healthy participants received behavioural training on discriminating phonetic contrasts within noise-vocoded speech for the 2 weeks between their two scans.

It is clearly shown neither of the boosting approaches employed manage to outperform a simple bagging model that is trained on presegmented phonetic data.

While remarkable performance improvements have been obtained with an MTR method, it has some drawbacks since it combines a number of noise conditions during training, which reduces the phonetic sharpness of the acoustic models in their probability density functions versus matched training where the training material is assumed to have the same noise condition as the noisy test speech.