AI models

LSTM

Classify, process and make predictions using LSTM on time series data as there are unknown duration between important events.

Applications
Time series forecast

Predict future values based on previous, sequential data and provide greater accuracy. Using this artificial recurrent neural network with deep learning can process entire sequences of data and learn long term sequences of observations, develop demand intelligence and provide forecast-grade data that can be used to train prediction models.

Speech Recognition

Various algorithms and computation techniques are used to recognize speech into text and improve its accuracy of transcription using statistical modeling systems with complex probability and mathematical functions to determine the most likely outcome.

Customised speech recognition models can be used along with acoustic models, a pronunciation dictionary, and language models to transcribe domain-specific terms and rare words by providing hints and improving transcription accuracy of specific words which powers virtual assistants, facilitating automated closed captioning, and enabling digital dictation platforms.

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