Examples of using Speech recognition in English and their translations into Serbian
{-}
-
Colloquial
-
Ecclesiastic
-
Computer
-
Latin
-
Cyrillic
AI functionality for data processing, linguistic analytics, speech recognition, and image recognition is already being utilized in a wide array of industries.
Speech recognition technologies continue to improve,
he continued working nevertheless by vocally recording his new works and using speech recognition programs.
In 2015, Google's speech recognition reportedly experienced a dramatic performance jump of 49% through CTC-trained LSTM, which they made
(Applause) In my very last example-- I do a lot of my work using speech recognition software.
In 2015, Google's large scale speech recognition suddenly almost doubled its performance through CTC-trained LSTM,
including computer vision, speech recognition, machine translation,
Rectified linear units find applications in computer vision[1] and speech recognition[10][11] using deep neural nets
Large-scale automatic speech recognition is the first and most convincing successful case
Speech recognition, visual perception,
The initial success in speech recognition was based on small-scale recognition tasks based on TIMIT.
including natural language processing, speech recognition, face recognition,
New research has zoomed in on the brain's speech recognition abilities, brain uses uncovering the mechanism through which the brain discerns between ambiguous sounds.
such as speech recognition, image recognition,
It is now also commonly used in speech recognition, speech synthesis,
Speech recognition and biometric authentication are great examples of a machine interacting with humans from an input perspective.
For example, in speech-to-text(speech recognition), the acoustic signal is treated as the observed sequence of events,
There is also a demo application for speech recognition and if you are interested, you can take a look.
Most speech recognition users would tend to agree that dictation machines can achieve very high performance in controlled conditions.
At about the same time, in late 2009, deep learning feedforward networks made inroads into speech recognition, as marked by the NIPS Workshop on Deep Learning for Speech Recognition. .